Reverse transcriptase template switching and false alternative transcripts

Machine Learning-Assisted Direct RNA Sequencing with Epigenetic RNA Modification Detection via Quantum Tunneling

RNA sequence information holds immense potential as a drug target for diagnosing various RNA-mediated diseases and viral/bacterial infections. Massively parallel complementary DNA (c-DNA) sequencing helps but results in a loss of valuable information about RNA modifications, which are often associated with cancer evolution. Herein, we report machine learning (ML)-assisted high throughput RNA sequencing with inherent RNA modification detection using a single-molecule, long-read, and label-free quantum tunneling approach. The ML tools achieve classification accuracy as high as 100% in decoding RNA and 98% for decoding both RNA and RNA modifications simultaneously. The relationships between input features and target values have been well examined through Shapley additive explanations. Furthermore, transmission and sensitivity readouts enable the recognition of RNA and its modifications with good selectivity and sensitivity. Our approach represents a starting point for ML-assisted direct RNA sequencing that can potentially decode RNA and its epigenetic modifications at the molecular level.

Computational approaches and challenges in the analysis of circRNA data

Circular RNAs (circRNA) are a class of non-coding RNA, forming a single-stranded covalently closed loop structure generated via back-splicing. Advancements in sequencing methods and technologies in conjunction with algorithmic developments of bioinformatics tools have enabled researchers to characterise the origin and function of circRNAs, with practical applications as a biomarker of diseases becoming increasingly relevant. Computational methods developed for circRNA analysis are predicated on detecting the chimeric back-splice junction of circRNAs whilst mitigating false-positive sequencing artefacts. In this review, we discuss in detail the computational strategies developed for circRNA identification, highlighting a selection of tool strengths, weaknesses and assumptions. In addition to circRNA identification tools, we describe methods for characterising the role of circRNAs within the competing endogenous RNA (ceRNA) network, their interactions with RNA-binding proteins, and publicly available databases for rich circRNA annotation.

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.

Experimental and analytical pipeline for sub-genomic RNA landscape of coronavirus by Nanopore sequencer

Coronaviruses (CoVs), including severe acute respiratory syndrome coronavirus 2, can infect a variety of mammalian and avian hosts with significant medical and economic consequences. During the life cycle of CoV, a coordinated series of subgenomic RNAs, including canonical subgenomic messenger RNA and non-canonical defective viral genomes (DVGs), are generated with different biological implications. Studies that adopted the Nanopore sequencer (ONT) to investigate the landscape and dynamics of viral RNA subgenomic transcriptomes applied arbitrary bioinformatics parameters without justification or experimental validation. The current study used bovine coronavirus (BCoV), which can be performed under biosafety level 2 for library construction and experimental validation using traditional colony polymerase chain reaction and Sanger sequencing. Four different ONT protocols, including RNA direct and cDNA direct sequencing with or without exonuclease treatment, were used to generate RNA transcriptomic libraries from BCoV-infected cell lysates. Through rigorously examining the k-mer, gap size, segment size, and bin size, the optimal cutoffs for the bioinformatic pipeline were determined to remove the sequence noise while keeping the informative DVG reads. The sensitivity and specificity of identifying DVG reads using the proposed pipeline can reach 82.6% and 99.6% under the k-mer size cutoff of 15. Exonuclease treatment reduced the abundance of RNA transcripts; however, it was not necessary for future library preparation. Additional recovery of clipped BCoV nucleotide sequences with experimental validation expands the landscape of the CoV discontinuous RNA transcriptome, whose biological function requires future investigation. The results of this study provide the benchmarks for library construction and bioinformatic parameters for studying the discontinuous CoV RNA transcriptome.IMPORTANCEFunctional defective viral genomic RNA, containing all the cis-acting elements required for translation or replication, may play different roles in triggering cell innate immune signaling, interfering with the canonical subgenomic messenger RNA transcription/translation or assisting in establishing persistence infection. This study does not only provide benchmarks for library construction and bioinformatic parameters for studying the discontinuous coronavirus RNA transcriptome but also reveals the complexity of the bovine coronavirus transcriptome, whose functional assays will be critical in future studies.

In search of critical dsRNA targets of ADAR1

Recent studies have underscored the pivotal role of adenosine-to-inosine RNA editing, catalyzed by ADAR1, in suppressing innate immune interferon responses triggered by cellular double-stranded RNA (dsRNA). However, the specific ADAR1 editing targets crucial for this regulatory function remain elusive. We review analyses of transcriptome-wide ADAR1 editing patterns and their evolutionary dynamics, which offer valuable insights into this unresolved query. The growing appreciation of the significance of immunogenic dsRNAs and their editing in inflammatory and autoimmune diseases and cancer calls for a more comprehensive understanding of dsRNA immunogenicity, which may promote our understanding of these diseases and open doors to therapeutic avenues.

Characterizing adjuvants' effects at murine immunoglobulin repertoire level

Generating large-scale, high-fidelity sequencing data is challenging and, furthermore, not much has been done to characterize adjuvants' effects at the repertoire level. Thus, we introduced an IgSeq pipeline that standardized library prep protocols and data analysis functions for accurate repertoire profiling. We then studied systemically effects of CpG and Alum on the Ig heavy chain repertoire using the ovalbumin (OVA) murine model. Ig repertoires of different tissues (spleen and bone marrow) and isotypes (IgG and IgM) were examined and compared in IGHV mutation, gene usage, CDR3 length, clonal diversity, and clonal selection. We found Ig repertoires of different compartments exhibited distinguishable profiles at the non-immunized steady state, and distinctions became more pronounced upon adjuvanted immunizations. Notably, Alum and CpG effects exhibited different tissue- and isotype-preferences. The former led to increased diversity of abundant clones in bone marrow, and the latter promoted the selection of IgG clones in both tissues.

Droplet Digital PCR for the Detection and Quantification of Bona Fide CircRNAs

CircRNAs are covalently closed RNA molecules gaining increasing attention over the years. Initially considered mere splicing errors, circRNAs are now recognized as a novel class of endogenous, conserved RNAs, expressed in many different species. The unique structure, the low levels of expression, and the almost complete sequence overlap with the cognate linear RNA make their detection and quantification challenging. Moreover, it has become crucial to prove the circular nature of the targeted transcript and unequivocally distinguish the circRNA from its linear counterpart. Nowadays, the most widely used technique to quantify circRNA expression is real-time quantitative PCR (qPCR). However, in the particular case of quantification of circles, it shows several technical shortcomings which affect the accuracy of the quantification. To precisely assess circRNA expression level, droplet digital PCR (ddPCR) is rapidly taking over for the more popular qPCR. In this chapter, we describe the detailed procedure based on droplets partitioning to quantify both linear and circRNA abundancy and demonstrate the circularity of the transcript under study with high precision, in a single experiment.

Circular RNAs: An emerging precise weapon for diabetic nephropathy diagnosis and therapy

Diabetic nephropathy (DN) is a prevalent chronic microvascular complication associated with diabetes mellitus and represents a major cause of chronic kidney disease and renal failure. Current treatment strategies for DN primarily focus on symptom alleviation, lacking effective approaches to halt or reverse DN progression. Circular RNA (circRNA), characterized by a closed-loop structure, has emerged as a novel non-coding RNA regulator of gene expression, attributed to its conservation, stability, specificity, and multifunctionality. Dysregulation of circRNA expression is closely associated with DN progression, whereby circRNA impacts kidney cell injury by modulating cell cycle, differentiation, cell death, as well as influencing the release of inflammatory factors and stromal fibronectin expression. Consequently, circRNA is considered a predictive biomarker and a potential therapeutic target for DN. This review provides an overview of the latest research progress in the classification, functions, monitoring methods, and databases related to circRNA. The paper focuses on elucidating the impact and underlying mechanisms of circRNA on kidney cells under diabetic conditions, aiming to offer novel insights into the prevention, diagnosis, and treatment of DN.

Identification and quantification of small exon-containing isoforms in long-read RNA sequencing data

Small exons are pervasive in transcriptomes across organisms, and their quantification in RNA isoforms is crucial for understanding gene functions. Although long-read RNA-seq based on Oxford Nanopore Technologies (ONT) offers the advantage of covering transcripts in full length, its lower base accuracy poses challenges for identifying individual exons, particularly microexons (≤ 30 nucleotides). Here, we systematically assess small exons quantification in synthetic and human ONT RNA-seq datasets. We demonstrate that reads containing small exons are often not properly aligned, affecting the quantification of relevant transcripts. Thus, we develop a local-realignment method for misaligned exons (MisER), which remaps reads with misaligned exons to the transcript references. Using synthetic and simulated datasets, we demonstrate the high sensitivity and specificity of MisER for the quantification of transcripts containing small exons. Moreover, MisER enabled us to identify small exons with a higher percent spliced-in index (PSI) in neural, particularly neural-regulated microexons, when comparing 14 neural to 16 non-neural tissues in humans. Our work introduces an improved quantification method for long-read RNA-seq and especially facilitates studies using ONT long-reads to elucidate the regulation of genes involving small exons.

dsRID: in silico identification of dsRNA regions using long-read RNA-seq data

MOTIVATION

Double-stranded RNAs (dsRNAs) are potent triggers of innate immune responses upon recognition by cytosolic dsRNA sensor proteins. Identification of endogenous dsRNAs helps to better understand the dsRNAome and its relevance to innate immunity related to human diseases.

RESULTS

Here, we report dsRID (double-stranded RNA identifier), a machine-learning-based method to predict dsRNA regions in silico, leveraging the power of long-read RNA-sequencing (RNA-seq) and molecular traits of dsRNAs. Using models trained with PacBio long-read RNA-seq data derived from Alzheimer's disease (AD) brain, we show that our approach is highly accurate in predicting dsRNA regions in multiple datasets. Applied to an AD cohort sequenced by the ENCODE consortium, we characterize the global dsRNA profile with potentially distinct expression patterns between AD and controls. Together, we show that dsRID provides an effective approach to capture global dsRNA profiles using long-read RNA-seq data.

AVAILABILITY AND IMPLEMENTATION

Software implementation of dsRID, and genomic coordinates of regions predicted by dsRID in all samples are available at the GitHub repository: https://github.com/gxiaolab/dsRID.

Merging short and stranded long reads improves transcript assembly

Long-read RNA sequencing has arisen as a counterpart to short-read sequencing, with the potential to capture full-length isoforms, albeit at the cost of lower depth. Yet this potential is not fully realized due to inherent limitations of current long-read assembly methods and underdeveloped approaches to integrate short-read data. Here, we critically compare the existing methods and develop a new integrative approach to characterize a particularly challenging pool of low-abundance long noncoding RNA (lncRNA) transcripts from short- and long-read sequencing in two distinct cell lines. Our analysis reveals severe limitations in each of the sequencing platforms. For short-read assemblies, coverage declines at transcript termini resulting in ambiguous ends, and uneven low coverage results in segmentation of a single transcript into multiple transcripts. Conversely, long-read sequencing libraries lack depth and strand-of-origin information in cDNA-based methods, culminating in erroneous assembly and quantitation of transcripts. We also discover a cDNA synthesis artifact in long-read datasets that markedly impacts the identity and quantitation of assembled transcripts. Towards remediating these problems, we develop a computational pipeline to "strand" long-read cDNA libraries that rectifies inaccurate mapping and assembly of long-read transcripts. Leveraging the strengths of each platform and our computational stranding, we also present and benchmark a hybrid assembly approach that drastically increases the sensitivity and accuracy of full-length transcript assembly on the correct strand and improves detection of biological features of the transcriptome. When applied to a challenging set of under-annotated and cell-type variable lncRNA, our method resolves the segmentation problem of short-read sequencing and the depth problem of long-read sequencing, resulting in the assembly of coherent transcripts with precise 5' and 3' ends. Our workflow can be applied to existing datasets for superior demarcation of transcript ends and refined isoform structure, which can enable better differential gene expression analyses and molecular manipulations of transcripts.

HIV-1 Vpr induces ciTRAN to prevent transcriptional repression of the provirus

The functional consequences of circular RNA (circRNA) expression on HIV-1 replication are largely unknown. Using a customized protocol involving direct RNA nanopore sequencing, here, we captured circRNAs from HIV-1-infected T cells and identified ciTRAN, a circRNA that modulates HIV-1 transcription. We found that HIV-1 infection induces ciTRAN expression in a Vpr-dependent manner and that ciTRAN interacts with SRSF1, a protein known to repress HIV-1 transcription. Our results suggest that HIV-1 hijacks ciTRAN to exclude serine/arginine-rich splicing factor 1 (SRSF1) from the viral transcriptional complex, thereby promoting efficient viral transcription. In addition, we demonstrate that an SRSF1-inspired mimic can inhibit viral transcription regardless of ciTRAN induction. The hijacking of a host circRNA thus represents a previously unknown facet of primate lentiviruses in overcoming transmission bottlenecks.

Detecting intragenic trans-splicing events from non-co-linearly spliced junctions by hybrid sequencing

Trans-spliced RNAs (ts-RNAs) are a type of non-co-linear (NCL) transcripts that consist of exons in an order topologically inconsistent with the corresponding DNA template. Detecting ts-RNAs is often interfered by experimental artifacts, circular RNAs (circRNAs) and genetic rearrangements. Particularly, intragenic ts-RNAs, which are derived from separate precursor mRNA molecules of the same gene, are often mistaken for circRNAs through analyses of RNA-seq data. Here we developed a bioinformatics pipeline (NCLscan-hybrid), which integrated short and long RNA-seq reads to minimize false positives and proposed out-of-circle and rolling-circle long reads to distinguish between intragenic ts-RNAs and circRNAs. Combining NCLscan-hybrid screening and multiple experimental validation steps successfully confirmed that four NCL events, which were previously regarded as circRNAs in databases, originated from trans-splicing. CRISPR-based endogenous genome modification experiments further showed that flanking intronic complementary sequences can significantly contribute to ts-RNA formation, providing an efficient/specific method to deplete ts-RNAs. We also experimentally validated that one ts-RNA (ts-ARFGEF1) played an important role for p53-mediated apoptosis through affecting the PERK/eIF2a/ATF4/CHOP signaling pathway in breast cancer cells. This study thus described both bioinformatics procedures and experimental validation steps for rigorous characterization of ts-RNAs, expanding future studies for identification, biogenesis, and function of these important but understudied transcripts.

L-GIREMI uncovers RNA editing sites in long-read RNA-seq

Although long-read RNA-seq is increasingly applied to characterize full-length transcripts it can also enable detection of nucleotide variants, such as genetic mutations or RNA editing sites, which is significantly under-explored. Here, we present an in-depth study to detect and analyze RNA editing sites in long-read RNA-seq. Our new method, L-GIREMI, effectively handles sequencing errors and read biases. Applied to PacBio RNA-seq data, L-GIREMI affords a high accuracy in RNA editing identification. Additionally, our analysis uncovered novel insights about RNA editing occurrences in single molecules and double-stranded RNA structures. L-GIREMI provides a valuable means to study nucleotide variants in long-read RNA-seq.

Artifacts and biases of the reverse transcription reaction in RNA sequencing

RNA sequencing has spurred a significant number of research areas in recent years. Most protocols rely on synthesizing a more stable complementary DNA (cDNA) copy of the RNA molecule during the reverse transcription reaction. The resulting cDNA pool is often wrongfully assumed to be quantitatively and molecularly similar to the original RNA input. Sadly, biases and artifacts confound the resulting cDNA mixture. These issues are often overlooked or ignored in the literature by those that rely on the reverse transcription process. In this review, we confront the reader with intra- and intersample biases and artifacts caused by the reverse transcription reaction during RNA sequencing experiments. To fight the reader's despair, we also provide solutions to most issues and inform on good RNA sequencing practices. We hope the reader can use this review to their advantage, thereby contributing to scientifically sound RNA studies.

Hybrid sequencing discloses unique aspects of the transcriptomic architecture in equid alphaherpesvirus 1

This study employed both short-read sequencing (SRS, Illumina) and long-read sequencing (LRS Oxford Nanopore Technologies) platforms to conduct a comprehensive analysis of the equid alphaherpesvirus 1 (EHV-1) transcriptome. The study involved the annotation of canonical mRNAs and their transcript variants, encompassing transcription start site (TSS) and transcription end site (TES) isoforms, in addition to alternative splicing forms. Furthermore, the study revealed the presence of numerous non-coding RNA (ncRNA) molecules, including intergenic and antisense transcripts, produced by EHV-1. An intriguing finding was the abundant production of chimeric transcripts, some of which potentially encode fusion polypeptides. Moreover, EHV-1 exhibited a greater incidence of transcriptional overlaps and splicing compared to related viruses. It is noteworthy that many genes have their unique TESs along with the co-terminal transcription ends, a characteristic scarcely seen in other alphaherpesviruses. The study also identified transcripts that overlap the replication origins of the virus. Moreover, a novel ncRNA, referred to as NOIR, was found to intersect with the 5'-ends of longer transcript isoform specified by the major transactivator genes ORF64 and ORF65, surrounding the OriL. These findings together imply the existence of a key regulatory mechanism that governs both transcription and replication through, among others, a process that involves interference between the DNA and RNA synthesis machineries.

dsRID: Editing-free in silico identification of dsRNA region using long-read RNA-seq data

Double-stranded RNAs (dsRNAs) are potent triggers of innate immune responses upon recognition by cytosolic dsRNA sensor proteins. Identification of endogenous dsRNAs helps to better understand the dsRNAome and its relevance to innate immunity related to human diseases. Here, we report dsRID (double-stranded RNA identifier), a machine learning-based method to predict dsRNA regions in silico, leveraging the power of long-read RNA-sequencing (RNA-seq) and molecular traits of dsRNAs. Using models trained with PacBio long-read RNA-seq data derived from Alzheimer's disease (AD) brain, we show that our approach is highly accurate in predicting dsRNA regions in multiple datasets. Applied to an AD cohort sequenced by the ENCODE consortium, we characterize the global dsRNA profile with potentially distinct expression patterns between AD and controls. Together, we show that dsRID provides an effective approach to capture global dsRNA profiles using long-read RNA-seq data.

The function and mechanisms of action of circular RNAs in Urologic Cancer

Kidney, bladder, and prostate cancer are the three major tumor types of the urologic system that seriously threaten human health. Circular RNAs (CircRNAs), special non-coding RNAs with a stabile structure and a unique back-splicing loop-forming ability, have received recent scientific attention. CircRNAs are widely distributed within the body, with important biologic functions such as sponges for microRNAs, as RNA binding proteins, and as templates for regulation of transcription and protein translation. The abnormal expression of circRNAs in vivo is significantly associated with the development of urologic tumors. CircRNAs have now emerged as potential biomarkers for the diagnosis and prognosis of urologic tumors, as well as targets for the development of new therapies. Although we have gained a better understanding of circRNA, there are still many questions to be answered. In this review, we summarize the properties of circRNAs and detail their function, focusing on the effects of circRNA on proliferation, metastasis, apoptosis, metabolism, and drug resistance in kidney, bladder, and prostate cancers.

Challenges and opportunities for circRNA identification and delivery

Circular RNAs (circRNAs) are evolutionarily conserved noncoding RNAs with tissue-specific expression patterns, and exert unique cellular functions that have the potential to become biomarkers in therapeutic applications. Therefore, accurate and sensitive detection of circRNA with facile platforms is essential for better understanding of circRNA biological processes and circRNA-related disease diagnosis and prognosis; and precise regulation of circRNA through efficient delivery of circRNA or siRNA is critical for therapeutic purposes. Here, we reviewed the current development of circRNA identification methodologies, including overviewing the purification steps, summarizing the sequencing methods of circRNA, as well as comparing the advantages and disadvantages of traditional and new detection methods. Then, we discussed the delivery and manipulation strategies for circRNAs in both research and clinic treatment. Finally, the challenges and opportunities of analyzing circRNAs were addressed.

Elevated atmospheric CO2 concentrations caused a shift of the metabolically active microbiome in vineyard soil

BACKGROUND

Elevated carbon dioxide concentrations (eCO₂), one of the main causes of climate change, have several consequences for both vine and cover crops in vineyards and potentially also for the soil microbiome. Hence soil samples were taken from a vineyard free-air CO₂ enrichment (VineyardFACE) study in Geisenheim and examined for possible changes in the soil active bacterial composition (cDNA of 16S rRNA) using a metabarcoding approach. Soil samples were taken from the areas between the rows of vines with and without cover cropping from plots exposed to either eCO₂ or ambient CO₂ (aCO₂).

RESULTS

Diversity indices and redundancy analysis (RDA) demonstrated that eCO₂ changed the active soil bacterial diversity in grapevine soil with cover crops (p-value 0.007). In contrast, the bacterial composition in bare soil was unaffected. In addition, the microbial soil respiration (p-values 0.04-0.003) and the ammonium concentration (p-value 0.003) were significantly different in the samples where cover crops were present and exposed to eCO₂. Moreover, under eCO₂ conditions, qPCR results showed a significant decrease in 16S rRNA copy numbers and transcripts for enzymes involved in N₂ fixation and NO₂^- reduction were observed using qPCR. Co-occurrence analysis revealed a shift in the number, strength, and patterns of microbial interactions under eCO₂ conditions, mainly represented by a reduction in the number of interacting ASVs and the number of interactions.

CONCLUSIONS

The results of this study demonstrate that eCO₂ concentrations changed the active soil bacterial composition, which could have future influence on both soil properties and wine quality.

Transcriptome diversity assessment of Gossypium arboreum (FDH228) leaves under control, drought and whitefly infestation using PacBio long reads

Alternative splicing (AS) and alternative polyadenylation (APA) are common mechanisms in eukaryotes to increase the complexity of transcriptomes and subsequently proteomes. Analysis of long reads transcriptomics data can result in the discovery of novel transcripts, splice sites, AS or APA events. Gossypium arboreum is an important cultivated cotton species and a putative contributor of the A sub-genome to the modern tetraploid cotton; and inherently tolerant to several biotic and abiotic stresses. Specifically, its variety 'FDH228' is considered to be an important resistance source. In this study, we sequenced the G. arboreum (var. FDH228) transcriptome using PacBio IsoSeq and illumina short read sequencing under three different conditions i.e. untreated/healthy, treated with biotic stress through whitefly infestation, and treated with abiotic stress via water deprivation, for the discovery and surveying of canonical and non-canonical AS, APA and transcript fusion events. We were able to obtain 15,419 unique transcripts from all samples representing 11,343 genes, out of which 10,832 were annotated and 520 were novel with respect to the published reference genome. These transcripts were grouped into different structural categories including 60 Antisense, 11,959 having a full-splice match, 999 with incomplete-splice match, 30 fusion transcripts, 177 genic, 479 intergenic, 771 novels in the catalog, and 944 Novel but not found in the catalog. Subsequently, randomly selected candidate transcripts were experimentally validated using qRT-PCR. Our comprehensive identification of canonical and non-canonical splicing events, and novel and fusion transcripts aids in the understanding of the resistance mechanisms for this specific germplasm.

A Multiplex Gene Expression Assay for Direct Measurement of RNA Transcripts in Crude Lysates of the Nematode Caenorhabditis elegans Used as a Bioanalytical Tool

Gene expression profiling in Caenorhabditis elegans has been demonstrated to be a potential bioanalytical tool to detect the toxic potency of environmental contaminants. The RNA transcripts of genes responding to toxic exposure can be used as biomarkers for detecting these toxins. For routine application in environmental quality monitoring, an easy-to-use multiplex assay is required to reliably quantify expression levels of these biomarkers. In the present study, a bead-based assay was developed to fingerprint gene expression in C. elegans by quantitating messenger RNAs (mRNAs) of multiple target genes directly from crude nematode lysates, circumventing RNA extraction and purification steps. The assay uses signal amplification rather than target amplification for direct measurement of toxin-induced RNA transcripts. Using a 50-gene panel, the expression changes of four candidate reference genes and 46 target mRNAs for various contaminants and wastewaters were successfully measured, and the expression profiles indicated the type of toxin present. Moreover, the multiplex assay response was in line with previous results obtained with more time-consuming reverse-transcription quantitative polymerase chain reaction and microarray analyses. In addition, the transcriptomic profiles of nematodes exposed to wastewater samples and extracts prepared from tissues of swimming crabs were evaluated. The profiles indicated the presence of organic pollutants. The present study illustrates the successful development of a multiplex fluorescent bead-based approach using nematode C. elegans crude lysates for gene expression profiling of target RNAs. This method can be used to routinely fingerprint the presence of toxic contaminants in environmental samples and to identify the most biologically active fraction of the contaminant mixture in a toxicity identification and evaluation approach. Environ Toxicol Chem 2023;42:130-142. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Identification of circular RNAs hosted by the RPGR ORF15 genomic locus

Mutations in the retina-specific isoform of the gene encoding retinitis pigmentosa GTPase regulator (RPGRorf15) cause X-linked retinitis pigmentosa, a severe and early onset inherited retinal degeneration. The underlying pathogenic mechanisms and variability in disease severity remain to be fully elucidated. The present study examines structural features of the ORF15 exonic region to provide new insights into the disease pathogenesis. Using canine and human RNA samples, we identified several novel RPGR ORF15-like linear RNA transcripts containing cryptic introns (exitrons) within the annotated exon ORF15. Furthermore, using outward-facing primers designed inside exitrons in the ORF15 exonic region, we found many of previously unidentified circular RNAs (circRNAs) that formed via back fusion of linear parts of the RPGRorf15 pre-mRNAs. These circRNAs (resistant to RNAse R treatment) were found in all studied cells and tissues. Notably, some circRNAs were present in cytoplasmic and polysomal RNA fractions. Although certain RPGR circRNAs may be cell type specific, we found some of the same circRNAs expressed in different cell types, suggesting similarities in their biogenesis and functions. Sequence analysis of RPGR circRNAs revealed several remarkable features, including identification of N6-methyladenosine (m6A) consensus sequence motifs and high prevalence of predictive microRNA binding sites pointing to the functional roles of these circRNAs. Our findings also illustrate the presence of non-canonical RPGR circRNA biogenesis pathways independent of the known back splicing mechanism. The obtained data on novel RPGR circRNAs further underline structural complexity of the RPGR ORF15 region and provide a potential molecular basis for the disease phenotypic heterogeneity.

An Update on Circular RNA in Pediatric Cancers

Circular RNAs (circRNAs) are a class of single-stranded closed noncoding RNA molecules which are formed as a result of reverse splicing of mRNAs. Despite their relative abundance, only recently there appeared an increased interest in the understanding of their regulatory importance. Among their most relevant characteristics are high stability, abundance and evolutionary conservation among species. CircRNAs are implicated in several cellular functions, ranging from miRNA and protein sponges to transcriptional modulation and splicing. Additionally, circRNAs' aberrant expression in pathological conditions is bringing to light their possible use as diagnostic and prognostic biomarkers. Their use as indicator molecules of pathological changes is also supported by their peculiar covalent closed cyclic structure which bestows resistance to RNases. Their regulatory role in cancer pathogenesis and metastasis is supported by studies involving human tumors that have investigated different expression profiles of these molecules. As endogenous competitive RNA, circRNAs can regulate tumor proliferation and invasion and they arouse great consideration as potential therapeutic biomarkers and targets for cancer. In this review, we describe the most recent findings on circRNAs in the most common pediatric solid cancers (such as brain tumors, neuroblastomas, and sarcomas) and in more rare ones (such as Wilms tumors, hepatoblastomas, and retinoblastomas).

Recent advances in cancer fusion transcript detection

Extensive investigation of gene fusions in cancer has led to the discovery of novel biomarkers and therapeutic targets. To date, most studies have neglected chromosomal rearrangement-independent fusion transcripts and complex fusion structures such as double or triple-hop fusions, and fusion-circRNAs. In this review, we untangle fusion-related terminology and propose a classification system involving both gene and transcript fusions. We highlight the importance of RNA-level fusions and how long-read sequencing approaches can improve detection and characterization. Moreover, we discuss novel bioinformatic tools to identify fusions in long-read sequencing data and strategies to experimentally validate and functionally characterize fusion transcripts.

Light-Seq: light-directed in situ barcoding of biomolecules in fixed cells and tissues for spatially indexed sequencing

We present Light-Seq, an approach for multiplexed spatial indexing of intact biological samples using light-directed DNA barcoding in fixed cells and tissues followed by ex situ sequencing. Light-Seq combines spatially targeted, rapid photocrosslinking of DNA barcodes onto complementary DNAs in situ with a one-step DNA stitching reaction to create pooled, spatially indexed sequencing libraries. This light-directed barcoding enables in situ selection of multiple cell populations in intact fixed tissue samples for full-transcriptome sequencing based on location, morphology or protein stains, without cellular dissociation. Applying Light-Seq to mouse retinal sections, we recovered thousands of differentially enriched transcripts from three cellular layers and discovered biomarkers for a very rare neuronal subtype, dopaminergic amacrine cells, from only four to eight individual cells per section. Light-Seq provides an accessible workflow to combine in situ imaging and protein staining with next generation sequencing of the same cells, leaving the sample intact for further analysis post-sequencing.

Light-Seq uses light-directed DNA barcoding in fixed cells and tissues for multiplexed spatial indexing and subsequent next generation sequencing. This approach blends spatial and omics information to enable analysis of rare cell types in complex tissues.

Click Chemistry Enables Rapid Amplification of Full-Length Reverse Transcripts for Long-Read Third Generation Sequencing

Here we describe the development of a novel click chemistry-based method for the generation and amplification of full-length cDNA libraries from total RNA, while avoiding the need for problematic template-switching (TS) reactions. Compared with prior efforts, our method involves neither random priming nor stochastic cDNA termination, thus enabling amplification of transcripts that were previously inaccessible via related click chemistry-based RNA sequencing techniques. A key modification involving the use of PCR primers containing two overhanging 3'-nucleotides substantially improved the read-through compatibility of the 1,4-disubstituted 1,2,3-triazole-containing cDNA, where such modifications typically hinder amplification. This allowed us to more than double the possible insert size compared with the state-of-the art click chemistry-based technique, PAC-seq. Furthermore, our method performed on par with a commercially available PCR-cDNA RNA sequencing kit, as determined by Oxford Nanopore sequencing. Given the known advantages of PAC-seq, namely, suppression of PCR artifacts, we anticipate that our contribution could enable diverse applications including improved analyses of mRNA splicing variants and fusion transcripts.

Long-Read Transcriptome of Equine Bronchoalveolar Cells

We used Pacific Biosciences long-read isoform sequencing to generate full-length transcript sequences in equine bronchoalveolar lavage fluid (BALF) cells. Our dataset consisted of 313,563 HiFi reads comprising 805 Mb of polished sequence information. The resulting equine BALF transcriptome consisted of 14,234 full-length transcript isoforms originating from 7017 unique genes. These genes consisted of 6880 previously annotated genes and 137 novel genes. We identified 3428 novel transcripts in addition to 10,806 previously known transcripts. These included transcripts absent from existing genome annotations, transcripts mapping to putative novel (unannotated) genes and fusion transcripts incorporating exons from multiple genes. We provide transcript-level data for equine BALF cells as a resource to the scientific community.

Transcriptomics and RNA-Based Therapeutics as Potential Approaches to Manage SARS-CoV-2 Infection

SARS-CoV-2 is a coronavirus family member that appeared in China in December 2019 and caused the disease called COVID-19, which was declared a pandemic in 2020 by the World Health Organization. In recent months, great efforts have been made in the field of basic and clinical research to understand the biology and infection processes of SARS-CoV-2. In particular, transcriptome analysis has contributed to generating new knowledge of the viral sequences and intracellular signaling pathways that regulate the infection and pathogenesis of SARS-CoV-2, generating new information about its biology. Furthermore, transcriptomics approaches including spatial transcriptomics, single-cell transcriptomics and direct RNA sequencing have been used for clinical applications in monitoring, detection, diagnosis, and treatment to generate new clinical predictive models for SARS-CoV-2. Consequently, RNA-based therapeutics and their relationship with SARS-CoV-2 have emerged as promising strategies to battle the SARS-CoV-2 pandemic with the assistance of novel approaches such as CRISPR-CAS, ASOs, and siRNA systems. Lastly, we discuss the importance of precision public health in the management of patients infected with SARS-CoV-2 and establish that the fusion of transcriptomics, RNA-based therapeutics, and precision public health will allow a linkage for developing health systems that facilitate the acquisition of relevant clinical strategies for rapid decision making to assist in the management and treatment of the SARS-CoV-2-infected population to combat this global public health problem.

BaRTv2: a highly resolved barley reference transcriptome for accurate transcript-specific RNA-seq quantification

Accurate characterisation of splice junctions (SJs) as well as transcription start and end sites in reference transcriptomes allows precise quantification of transcripts from RNA-seq data, and enables detailed investigations of transcriptional and post-transcriptional regulation. Using novel computational methods and a combination of PacBio Iso-seq and Illumina short-read sequences from 20 diverse tissues and conditions, we generated a comprehensive and highly resolved barley reference transcript dataset from the European 2-row spring barley cultivar Barke (BaRTv2.18). Stringent and thorough filtering was carried out to maintain the quality and accuracy of the SJs and transcript start and end sites. BaRTv2.18 shows increased transcript diversity and completeness compared with an earlier version, BaRTv1.0. The accuracy of transcript level quantification, SJs and transcript start and end sites have been validated extensively using parallel technologies and analysis, including high-resolution reverse transcriptase-polymerase chain reaction and 5'-RACE. BaRTv2.18 contains 39 434 genes and 148 260 transcripts, representing the most comprehensive and resolved reference transcriptome in barley to date. It provides an important and high-quality resource for advanced transcriptomic analyses, including both transcriptional and post-transcriptional regulation, with exceptional resolution and precision.

Detection of Chimeric Cellular: HIV mRNAs Generated Through Aberrant Splicing in HIV-1 Latently Infected Resting CD4+ T Cells

Latent HIV-1 provirus in infected individuals on suppressive therapy does not always remain transcriptionally silent. Both HIV-1 LTR and human gene promoter derived transcriptional events can contribute HIV-1 sequences to the mRNA produced in the cell. In addition, chimeric cellular:HIV mRNA can arise through readthrough transcription and aberrant splicing. Using target enrichment coupled to the Illumina Mi-Seq and PacBio RS II platforms, we show that 3’ LTR activation is frequent in latently infected cells from both the CCL19-induced primary cell model of HIV-1 latency as well as ex vivo samples. In both systems of latent HIV-1 infection, we detected several chimeric species that were generated via activation of a cryptic splice donor site in the 5’ LTR of HIV-1. Aberrant splicing involving the major HIV-1 splice donor sites, SD1 and SD4 disrupts post-transcriptional processing of the gene in which HIV-1 is integrated. In the primary cell model of HIV-1 latency, Tat-encoding sequences are incorporated into the chimeric mRNA transcripts through the use of SD4. Our study unravels clues to the characteristics of HIV-1 integrants that promote formation of chimeric cellular:HIV mRNA and improves the understanding of the HIV-1 RNA footprint in latently infected cells.

Elevated Atmospheric CO2 Modifies Mostly the Metabolic Active Rhizosphere Soil Microbiome in the Giessen FACE Experiment

Elevated levels of atmospheric CO2 lead to the increase of plant photosynthetic rates, carbon inputs into soil and root exudation. In this work, the effects of rising atmospheric CO2 levels on the metabolic active soil microbiome have been investigated at the Giessen free-air CO2 enrichment (Gi-FACE) experiment on a permanent grassland site near Giessen, Germany. The aim was to assess the effects of increased C supply into the soil, due to elevated CO2, on the active soil microbiome composition. RNA extraction and 16S rRNA (cDNA) metabarcoding sequencing were performed from bulk and rhizosphere soils, and the obtained data were processed for a compositional data analysis calculating diversity indices and differential abundance analyses. The structure of the metabolic active microbiome in the rhizospheric soil showed a clear separation between elevated and ambient CO2 (p = 0.002); increased atmospheric CO2 concentration exerted a significant influence on the microbiomes differentiation (p = 0.01). In contrast, elevated CO2 had no major influence on the structure of the bulk soil microbiome (p = 0.097). Differential abundance results demonstrated that 42 bacterial genera were stimulated under elevated CO2. The RNA-based metabarcoding approach used in this research showed that the ongoing atmospheric CO2 increase of climate change will significantly shift the microbiome structure in the rhizosphere.

Genion, an accurate tool to detect gene fusion from long transcriptomics reads

BACKGROUND

The advent of next-generation sequencing technologies empowered a wide variety of transcriptomics studies. A widely studied topic is gene fusion which is observed in many cancer types and suspected of having oncogenic properties. Gene fusions are the result of structural genomic events that bring two genes closely located and result in a fused transcript. This is different from fusion transcripts created during or after the transcription process. These chimeric transcripts are also known as read-through and trans-splicing transcripts. Gene fusion discovery with short reads is a well-studied problem, and many methods have been developed. But the sensitivity of these methods is limited by the technology, especially the short read length. Advances in long-read sequencing technologies allow the generation of long transcriptomics reads at a low cost. Transcriptomic long-read sequencing presents unique opportunities to overcome the shortcomings of short-read technologies for gene fusion detection while introducing new challenges.

RESULTS

We present Genion, a sensitive and fast gene fusion detection method that can also detect read-through events. We compare Genion against a recently introduced long-read gene fusion discovery method, LongGF, both on simulated and real datasets. On simulated data, Genion accurately identifies the gene fusions and its clustering accuracy for detecting fusion reads is better than LongGF. Furthermore, our results on the breast cancer cell line MCF-7 show that Genion correctly identifies all the experimentally validated gene fusions.

CONCLUSIONS

Genion is an accurate gene fusion caller. Genion is implemented in C++ and is available at https://github.com/vpc-ccg/genion .

Identification of high-confidence human poly(A) RNA isoform scaffolds using nanopore sequencing

Nanopore sequencing devices read individual RNA strands directly. This facilitates identification of exon linkages and nucleotide modifications; however, using conventional direct RNA nanopore sequencing, the 5' and 3' ends of poly(A) RNA cannot be identified unambiguously. This is due in part to RNA degradation in vivo and in vitro that can obscure transcription start and end sites. In this study, we aimed to identify individual full-length human RNA isoforms among ∼4 million nanopore poly(A)-selected RNA reads. First, to identify RNA strands bearing 5' m⁷G caps, we exchanged the biological cap for a modified cap attached to a 45-nt oligomer. This oligomer adaptation method improved 5' end sequencing and ensured correct identification of the 5' m⁷G capped ends. Second, among these 5'-capped nanopore reads, we screened for features consistent with a 3' polyadenylation site. Combining these two steps, we identified 294,107 individual high-confidence full-length RNA scaffolds from human GM12878 cells, most of which (257,721) aligned to protein-coding genes. Of these, 4876 scaffolds indicated unannotated isoforms that were often internal to longer, previously identified RNA isoforms. Orthogonal data for m⁷G caps and open chromatin, such as CAGE and DNase-HS seq, confirmed the validity of these high-confidence RNA scaffolds.

Circular RNA detection methods: A minireview

Circular RNA (circRNA), a novel type of covalently closed RNA, is implicated in several developmental and metabolic disease processes. CircRNAs exhibit tissue-specific expression, and are stable, abundant, and highly conserved, making them ideal biomarkers for diagnosis and prognosis. Accurate profiling of circRNA, however, is a prerequisite for their clinical application. Traditional methods such as northern blotting, RT-qPCR, and microarray analysis provide useful but limited information. To address these issues, a number of novel assays have recently emerged, such as droplet digital PCR (ddPCR), isothermal exponential amplification, and rolling cycle amplification, which increase the sensitivity and specificity of circRNA detection. Herein, we summarize the advantages and limitations of the new detection methods and discuss the challenges as well as future directions.

Library-based analysis reveals segment and length dependent characteristics of defective influenza genomes

Found in a diverse set of viral populations, defective interfering particles are parasitic variants that are unable to replicate on their own yet rise to relatively high frequencies. Their presence is associated with a loss of population fitness, both through the depletion of key cellular resources and the stimulation of innate immunity. For influenza A virus, these particles contain large internal deletions in the genomic segments which encode components of the heterotrimeric polymerase. Using a library-based approach, we comprehensively profile the growth and replication of defective influenza species, demonstrating that they possess an advantage during genome replication, and that exclusion during population expansion reshapes population composition in a manner consistent with their final, observed, distribution in natural populations. We find that an innate immune response is not linked to the size of a deletion; however, replication of defective segments can enhance their immunostimulatory properties. Overall, our results address several key questions in defective influenza A virus biology, and the methods we have developed to answer those questions may be broadly applied to other defective viruses.

Nanopore sequencing of single-cell transcriptomes with scCOLOR-seq

Here we describe single-cell corrected long-read sequencing (scCOLOR-seq), which enables error correction of barcode and unique molecular identifier oligonucleotide sequences and permits standalone cDNA nanopore sequencing of single cells. Barcodes and unique molecular identifiers are synthesized using dimeric nucleotide building blocks that allow error detection. We illustrate the use of the method for evaluating barcode assignment accuracy, differential isoform usage in myeloma cell lines, and fusion transcript detection in a sarcoma cell line.

The human TRAM1 locus expresses circular RNAs

Numerous indirect and in silico produced evidences suggest circular RNAs (circRNA) in mammals while thorough experimental proofs of their existence have rarely been reported. Biological studies of circRNA, however, should be based on experimentally verified circRNAs. Here, we describe the identification of two circRNAs originating from the gene locus of the translocation associated membrane protein 1 (TRAM1). Linear and potentially circular TRAM1-specific transcripts were identified in a transcriptome analysis of urine RNA of bladder cancer (BCa) patients versus healthy donors. Thus, we first focused on the topology of TRAM1-specific transcripts. We describe conclusive experimental evidence for the existence of TRAM1-specific circRNAs in the human BCa cell lines ECV-304 and RT-4. PCR-based methodology followed by cloning and sequencing strongly indicated the circular topology of two TRAM1 RNAs. Further, studies with exon fusion sequence-specific antisense oligonucleotides (asON) and RNase H as well as studies in the use of RNase R contribute to conclusive set of experiments supporting the circular topology of TRAM1 transcripts. On the biological side, TRAM1-specific circRNAs showed low expression levels and minor differences in BCa cell lines while linear TRAM1 transcripts displayed down-regulated expression in the higher cancer stage model ECV-304 versus more differentiated RT-4 cells.

The Use of circRNAs as Biomarkers of Cancer

CircRNAs are a subclass of lncRNAs that have been found to be abundantly present in a wide range of species, including humans. CircRNAs are generally produced by a noncanonical splicing event called backsplicing that is dependent on the canonical splicing machinery, giving rise to circRNAs classified into three main categories: exonic circRNA, circular intronic RNA, and exon-intron circular RNA. Notably, circRNAs possess functional importance and display their functions through different mechanisms of action including sponging miRNAs, or even being translated into functional proteins. In addition, circRNAs also have great potential as biomarkers, particularly in cancer, thanks to their high stability, tissue type and developmental stage specificity, and their presence in biological fluids, which make them promising candidates as noninvasive biomarkers. In this chapter, we describe the most commonly used techniques for the study of circRNAs as cancer biomarkers, including high-throughput techniques such as RNA-Seq and microarrays, and other methods to analyze the presence of specific circRNAs in patient samples.

CircRNAs and their regulatory roles in cancers

Circular RNAs (circRNAs), a novel type of non-coding RNAs (ncRNAs), have a covalently closed circular structure resulting from pre-mRNA back splicing via spliceosome and ribozymes. They can be classified differently in accordance with different criteria. As circRNAs are abundant, conserved, and stable, they can be used as diagnostic markers in various diseases and targets to develop new therapies. There are various functions of circRNAs, including sponge for miR/proteins, role of scaffolds, templates for translation, and regulators of mRNA translation and stability. Without m7G cap and poly-A tail, circRNAs can still be degraded in several ways, including RNase L, Ago-dependent, and Ago-independent degradation. Increasing evidence indicates that circRNAs can be modified by N-6 methylation (m6A) in many aspects such as biogenesis, nuclear export, translation, and degradation. In addition, they have been proved to play a regulatory role in the progression of various cancers. Recently, methods of detecting circRNAs with high sensitivity and specificity have also been reported. This review presents a detailed overview of circRNAs regarding biogenesis, biomarker, functions, degradation, and dynamic modification as well as their regulatory roles in various cancers. It’s particularly summarized in detail in the biogenesis of circRNAs, regulation of circRNAs by m6A modification and mechanisms by which circRNAs affect tumor progression respectively. Moreover, existing circRNA detection methods and their characteristics are also mentioned.

PacBio Iso-Seq Improves the Rainbow Trout Genome Annotation and Identifies Alternative Splicing Associated With Economically Important Phenotypes

Rainbow trout is an important model organism that has received concerted international efforts to study the transcriptome. For this purpose, short-read sequencing has been primarily used over the past decade. However, these sequences are too short of resolving the transcriptome complexity. This study reported a first full-length transcriptome assembly of the rainbow trout using single-molecule long-read isoform sequencing (Iso-Seq). Extensive computational approaches were used to refine and validate the reconstructed transcriptome. The study identified 10,640 high-confidence transcripts not previously annotated, in addition to 1,479 isoforms not mapped to the current Swanson reference genome. Most of the identified lncRNAs were non-coding variants of coding transcripts. The majority of genes had multiple transcript isoforms (average ∼3 isoforms/locus). Intron retention (IR) and exon skipping (ES) accounted for 56% of alternative splicing (AS) events. Iso-Seq improved the reference genome annotation, which allowed identification of characteristic AS associated with fish growth, muscle accretion, disease resistance, stress response, and fish migration. For instance, an ES in GVIN1 gene existed in fish susceptible to bacterial cold-water disease (BCWD). Besides, under five stress conditions, there was a commonly regulated exon in prolyl 4-hydroxylase subunit alpha-2 (P4HA2) gene. The reconstructed gene models and their posttranscriptional processing in rainbow trout provide invaluable resources that could be further used for future genetics and genomics studies. Additionally, the study identified characteristic transcription events associated with economically important phenotypes, which could be applied in selective breeding.

Host-Virus Chimeric Events in SARS-CoV-2-Infected Cells Are Infrequent and Artifactual

The pathogenic mechanisms underlying severe SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infection remain largely unelucidated. High-throughput sequencing technologies that capture genome and transcriptome information are key approaches to gain detailed mechanistic insights from infected cells. These techniques readily detect both pathogen- and host-derived sequences, providing a means of studying host-pathogen interactions. Recent studies have reported the presence of host-virus chimeric (HVC) RNA in transcriptome sequencing (RNA-seq) data from SARS-CoV-2-infected cells and interpreted these findings as evidence of viral integration in the human genome as a potential pathogenic mechanism. Since SARS-CoV-2 is a positive-sense RNA virus that replicates in the cytoplasm, it does not have a nuclear phase in its life cycle. Thus, it is biologically unlikely to be in a location where splicing events could result in genome integration. Therefore, we investigated the biological authenticity of HVC events. In contrast to true biological events like mRNA splicing and genome rearrangement events, which generate reproducible chimeric sequencing fragments across different biological isolates, we found that HVC events across >100 RNA-seq libraries from patients with coronavirus disease 2019 (COVID-19) and infected cell lines were highly irreproducible. RNA-seq library preparation is inherently error prone due to random template switching during reverse transcription of RNA to cDNA. By counting chimeric events observed when constructing an RNA-seq library from human RNA and spiked-in RNA from an unrelated species, such as the fruit fly, we estimated that ∼1% of RNA-seq reads are artifactually chimeric. In SARS-CoV-2 RNA-seq, we found that the frequency of HVC events was, in fact, not greater than this background "noise." Finally, we developed a novel experimental approach to enrich SARS-CoV-2 sequences from bulk RNA of infected cells. This method enriched viral sequences but did not enrich HVC events, suggesting that the majority of HVC events are, in all likelihood, artifacts of library construction. In conclusion, our findings indicate that HVC events observed in RNA-sequencing libraries from SARS-CoV-2-infected cells are extremely rare and are likely artifacts arising from random template switching of reverse transcriptase and/or sequence alignment errors. Therefore, the observed HVC events do not support SARS-CoV-2 fusion to cellular genes and/or integration into human genomes. IMPORTANCE The pathogenic mechanisms underlying SARS-CoV-2, the virus responsible for COVID-19, are not fully understood. In particular, relatively little is known about the reasons some individuals develop life-threatening or persistent COVID-19. Recent studies identified host-virus chimeric (HVC) reads in RNA-sequencing data from SARS-CoV-2-infected cells and suggested that HVC events support potential "human genome invasion" and "integration" by SARS-CoV-2. This suggestion has fueled concerns about the long-term effects of current mRNA vaccines that incorporate elements of the viral genome. SARS-CoV-2 is a positive-sense, single-stranded RNA virus that does not encode a reverse transcriptase and does not include a nuclear phase in its life cycle, so some doubts have rightfully been expressed regarding the authenticity of HVCs and the role played by endogenous retrotransposons in this phenomenon. Thus, it is important to independently authenticate these HVC events. Here, we provide several lines of evidence suggesting that the observed HVC events are likely artifactual.

Direct long-read RNA sequencing identifies a subset of questionable exitrons likely arising from reverse transcription artifacts

Resistance to CD19-directed immunotherapies in lymphoblastic leukemia has been attributed, among other factors, to several aberrant CD19 pre-mRNA splicing events, including recently reported excision of a cryptic intron embedded within CD19 exon 2. While "exitrons" are known to exist in hundreds of human transcripts, we discovered, using reporter assays and direct long-read RNA sequencing (dRNA-seq), that the CD19 exitron is an artifact of reverse transcription. Extending our analysis to publicly available datasets, we identified dozens of questionable exitrons, dubbed "falsitrons," that appear only in cDNA-seq, but never in dRNA-seq. Our results highlight the importance of dRNA-seq for transcript isoform validation.

Comparative physiological and full-length transcriptome analyses reveal the molecular mechanism of melatonin-mediated salt tolerance in okra (Abelmoschus esculentus L.)

BACKGROUND

Melatonin, a multifunctional signal molecule, has been reported to play crucial roles in growth and development and stress responses in various plant species. Okra (Abelmoschus esculentus L.) is a food crop with extremely high values of nutrition and healthcare. Recent reports have revealed the protective role of melatonin in alleviating salt stress. However, little is known about its regulatory mechanisms in response to salt stress in okra.

RESULTS

In this study, we explored whether exogenous melatonin pretreatment could alleviate salt stress (300 mM NaCl) of okra plants. Results showed that exogenous application of melatonin (50 μM) significantly enhanced plant tolerance to salt stress, as demonstrated by the plant resistant phenotype, as well as by the higher levels of the net photosynthetic rate, chlorophyll fluorescence and chlorophyll content in comparison with nontreated salt-stressed plants. Additionally, melatonin pretreatment remarkably decreased the levels of lipid peroxidation and H₂O₂ content and scavenged O₂^•- in melatonin-pretreated plants, which may be attributed to the higher levels of enzyme activities including POD and GR. Moreover, a combination of third- (PacBio) and second-generation (Illumina) sequencing technologies was applied to sequence full-length transcriptomes of okra. A total of 121,360 unigenes was obtained, and the size of transcript lengths ranged from 500 to 6000 bp. Illumina RNA-seq analysis showed that: Comparing with control, 1776, 1063 and 1074 differential expression genes (DEGs) were identified from the three treatments (NaCl, MT50 and MT + NaCl, respectively). These genes were enriched in more than 10 GO terms and 34 KEGG pathways. Nitrogen metabolism, sulfur metabolism, and alanine, aspartate and glutamate metabolism were significantly enriched in all three treatments. Many transcription factors including MYB, WRKY, NAC etc., were also identified as DEGs.

CONCLUSIONS

Our preliminary results suggested that melatonin pretreatment enhanced salt tolerance of okra plants for the first time. These data provide the first set of full-length isoforms in okra and more comprehensive insights into the molecular mechanism of melatonin responses to salt stress.

Genomics as a potential tool to unravel the rhizosphere microbiome interactions on plant health

Intense agricultural practices to meet rising food demands have caused ecosystem perturbations. For sustainable crop production, biological agents are gaining attention, but exploring their functional potential on a multi-layered complex ecosystem like the rhizosphere is challenging. This review explains the significance of genomics as a culture-independent molecular tool to understand the diversity and functional significance of the rhizosphere microbiome for sustainable agriculture. It discusses the recent significant studies in the rhizosphere environment carried out using evolving techniques like metagenomics, metatranscriptomics, and metaproteomics, their challenges, constraints infield application, and prospective solutions. The recent advances in techniques such as nanotechnology for the development of bioformulations and visualization techniques contemplating environmental safety were also discussed. The need for development of metagenomic data sets of regionally important crops, their plant microbial interactions and agricultural practices for narrowing down significant data from huge databases have been suggested. The role of taxonomical and functional diversity of soil microbiota in understanding soil suppression and part played by the microbial metabolites in the process have been analyzed and discussed in the context of 'omics' approach. 'Omics' studies have revealed important information about microbial diversity, their responses to various biotic and abiotic stimuli, and the physiology of disease suppression. This can be translated to crop sustainability and combinational approaches with advancing visualization and analysis methodologies fix the existing knowledge gap to a huge extend. With improved data processing and standardization of the methods, details of plant-microbe interactions can be successfully decoded to develop sustainable agricultural practices.

An Integrated Sequencing Approach for Updating the Pseudorabies Virus Transcriptome

In the last couple of years, the implementation of long-read sequencing (LRS) technologies for transcriptome profiling has uncovered an extreme complexity of viral gene expression. In this study, we carried out a systematic analysis on the pseudorabies virus transcriptome by combining our current data obtained by using Pacific Biosciences Sequel and Oxford Nanopore Technologies MinION sequencing with our earlier data generated by other LRS and short-read sequencing techniques. As a result, we identified a number of novel genes, transcripts, and transcript isoforms, including splice and length variants, and also confirmed earlier annotated RNA molecules. One of the major findings of this study is the discovery of a large number of 5′-truncations of larger putative mRNAs being 3′-co-terminal with canonical mRNAs of PRV. A large fraction of these putative RNAs contain in-frame ATGs, which might initiate translation of N-terminally truncated polypeptides. Our analyses indicate that CTO-S, a replication origin-associated RNA molecule is expressed at an extremely high level. This study demonstrates that the PRV transcriptome is much more complex than previously appreciated.

Host-virus chimeric events in SARS-CoV2 infected cells are infrequent and artifactual

Pathogenic mechanisms underlying severe SARS-CoV2 infection remain largely unelucidated. High throughput sequencing technologies that capture genome and transcriptome information are key approaches to gain detailed mechanistic insights from infected cells. These techniques readily detect both pathogen and host-derived sequences, providing a means of studying host-pathogen interactions. Recent studies have reported the presence of host-virus chimeric (HVC) RNA in RNA-seq data from SARS-CoV2 infected cells and interpreted these findings as evidence of viral integration in the human genome as a potential pathogenic mechanism. Since SARS-CoV2 is a positive sense RNA virus that replicates in the cytoplasm it does not have a nuclear phase in its life cycle, it is biologically unlikely to be in a location where splicing events could result in genome integration. Here, we investigated the biological authenticity of HVC events. In contrast to true biological events such as mRNA splicing and genome rearrangement events, which generate reproducible chimeric sequencing fragments across different biological isolates, we found that HVC events across >100 RNA-seq libraries from patients with COVID-19 and infected cell lines, were highly irreproducible. RNA-seq library preparation is inherently error-prone due to random template switching during reverse transcription of RNA to cDNA. By counting chimeric events observed when constructing an RNA-seq library from human RNA and spike-in RNA from an unrelated species, such as fruit-fly, we estimated that ~1% of RNA-seq reads are artifactually chimeric. In SARS-CoV2 RNA-seq we found that the frequency of HVC events was, in fact, not greater than this background “noise”. Finally, we developed a novel experimental approach to enrich SARS-CoV2 sequences from bulk RNA of infected cells. This method enriched viral sequences but did not enrich for HVC events, suggesting that the majority of HVC events are, in all likelihood, artifacts of library construction. In conclusion, our findings indicate that HVC events observed in RNA-sequencing libraries from SARS-CoV2 infected cells are extremely rare and are likely artifacts arising from either random template switching of reverse-transcriptase and/or sequence alignment errors. Therefore, the observed HVC events do not support SARS-CoV2 fusion to cellular genes and/or integration into human genomes.

Profiling of circRNAs using an enzyme-free digital counting method

Circular RNAs (circRNAs) have recently gained substantial attention as potential biomarkers in several human diseases, most prominently in cancer. However, the detection and quantification of circRNA biomarkers pose specific challenges owing to their circular nature. In particular, the use of enzymes, such as reverse transcriptases, may lead to impaired quantification, poor interlaboratory reproducibility and even false-positive results. Therefore, the development of methods for accurate quantification of circRNA biomarkers is a high priority. An enzyme-free and digital quantification method, named NanoString nCounter, was recently adapted for circRNA detection. In this review, I describe the advantages of using this technology for circRNA quantification as well as methodological considerations, potential pitfalls and disadvantages.