The Architecture of SARS-CoV-2 Transcriptome.

SARS-CoV-2 is a betacoronavirus responsible for the COVID-19 pandemic. Although the SARS-CoV-2 genome was reported recently, its transcriptomic architecture is unknown. Utilizing two complementary sequencing techniques, we present a high-resolution map of the SARS-CoV-2 transcriptome and epitranscriptome. DNA nanoball sequencing shows that the transcriptome is highly complex owing to numerous discontinuous transcription events. In addition to the canonical genomic and 9 subgenomic RNAs, SARS-CoV-2 produces transcripts encoding unknown ORFs with fusion, deletion, and/or frameshift. Using nanopore direct RNA sequencing, we further find at least 41 RNA modification sites on viral transcripts, with the most frequent motif, AAGAA. Modified RNAs have shorter poly(A) tails than unmodified RNAs, suggesting a link between the modification and the 3' tail. Functional investigation of the unknown transcripts and RNA modifications discovered in this study will open new directions to our understanding of the life cycle and pathogenicity of SARS-CoV-2.

2'-O-methylation at internal sites on mRNA promotes mRNA stability.

2'-O-methylation (Nm) is a prominent RNA modification well known in noncoding RNAs and more recently also found at many mRNA internal sites. However, their function and base-resolution stoichiometry remain underexplored. Here, we investigate the transcriptome-wide effect of internal site Nm on mRNA stability. Combining nanopore sequencing with our developed machine learning method, NanoNm, we identify thousands of Nm sites on mRNAs with a single-base resolution. We observe a positive effect of FBL-mediated Nm modification on mRNA stability and expression level. Elevated FBL expression in cancer cells is associated with increased expression levels for 2'-O-methylated mRNAs of cancer pathways, implying the role of FBL in post-transcriptional regulation. Lastly, we find that FBL-mediated 2'-O-methylation connects to widespread 3' UTR shortening, a mechanism that globally increases RNA stability. Collectively, we demonstrate that FBL-mediated Nm modifications at mRNA internal sites regulate gene expression by enhancing mRNA stability.

Single-molecule mapping of replisome progression.

Fundamental aspects of DNA replication, such as the anatomy of replication stall sites, how replisomes are influenced by gene transcription, and whether the progression of sister replisomes is coordinated, are poorly understood. Available techniques do not allow the precise mapping of the positions of individual replisomes on chromatin. We have developed a method called Replicon-seq that entails the excision of full-length replicons by controlled nuclease cleavage at replication forks. Replicons are sequenced using Nanopore, which provides a single-molecule readout of long DNA. Using Replicon-seq, we found that sister replisomes function autonomously and yet progress through chromatin with remarkable consistency. Replication forks that encounter obstacles pause for a short duration but rapidly resume synthesis. The helicase Rrm3 plays a critical role both in mitigating the effect of protein barriers and with facilitating efficient termination. Replicon-seq provides a high-resolution means of defining how individual replisomes move across the genome.

The SARS-CoV-2 subgenome landscape and its novel regulatory features.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is currently a global pandemic. CoVs are known to generate negative subgenomes (subgenomic RNAs [sgRNAs]) through transcription-regulating sequence (TRS)-dependent template switching, but the global dynamic landscapes of coronaviral subgenomes and regulatory rules remain unclear. Here, using next-generation sequencing (NGS) short-read and Nanopore long-read poly(A) RNA sequencing in two cell types at multiple time points after infection with SARS-CoV-2, we identified hundreds of template switches and constructed the dynamic landscapes of SARS-CoV-2 subgenomes. Interestingly, template switching could occur in a bidirectional manner, with diverse SARS-CoV-2 subgenomes generated from successive template-switching events. The majority of template switches result from RNA-RNA interactions, including seed and compensatory modes, with terminal pairing status as a key determinant. Two TRS-independent template switch modes are also responsible for subgenome biogenesis. Our findings reveal the subgenome landscape of SARS-CoV-2 and its regulatory features, providing a molecular basis for understanding subgenome biogenesis and developing novel anti-viral strategies.

Targeting the m6A RNA modification pathway blocks SARS-CoV-2 and HCoV-OC43 replication.

N6-methyladenosine (m6A) is an abundant internal RNA modification, influencing transcript fate and function in uninfected and virus-infected cells. Installation of m6A by the nuclear RNA methyltransferase METTL3 occurs cotranscriptionally; however, the genomes of some cytoplasmic RNA viruses are also m6A-modified. How the cellular m6A modification machinery impacts coronavirus replication, which occurs exclusively in the cytoplasm, is unknown. Here we show that replication of SARS-CoV-2, the agent responsible for the COVID-19 pandemic, and a seasonal human ß-coronavirus HCoV-OC43, can be suppressed by depletion of METTL3 or cytoplasmic m6A reader proteins YTHDF1 and YTHDF3 and by a highly specific small molecule METTL3 inhibitor. Reduction of infectious titer correlates with decreased synthesis of viral RNAs and the essential nucleocapsid (N) protein. Sites of m6A modification on genomic and subgenomic RNAs of both viruses were mapped by methylated RNA immunoprecipitation sequencing (meRIP-seq). Levels of host factors involved in m6A installation, removal, and recognition were unchanged by HCoV-OC43 infection; however, nuclear localization of METTL3 and cytoplasmic m6A readers YTHDF1 and YTHDF2 increased. This establishes that coronavirus RNAs are m6A-modified and host m6A pathway components control ß-coronavirus replication. Moreover, it illustrates the therapeutic potential of targeting the m6A pathway to restrict coronavirus reproduction.

Nanopore Sequencing Enables Comprehensive Transposable Element Epigenomic Profiling.

Transposable elements (TEs) drive genome evolution and are a notable source of pathogenesis, including cancer. While CpG methylation regulates TE activity, the locus-specific methylation landscape of mobile human TEs has to date proven largely inaccessible. Here, we apply new computational tools and long-read nanopore sequencing to directly infer CpG methylation of novel and extant TE insertions in hippocampus, heart, and liver, as well as paired tumor and non-tumor liver. As opposed to an indiscriminate stochastic process, we find pronounced demethylation of young long interspersed element 1 (LINE-1) retrotransposons in cancer, often distinct to the adjacent genome and other TEs. SINE-VNTR-Alu (SVA) retrotransposons, including their internal tandem repeat-associated CpG island, are near-universally methylated. We encounter allele-specific TE methylation and demethylation of aberrantly expressed young LINE-1s in normal tissues. Finally, we recover the complete sequences of tumor-specific LINE-1 insertions and their retrotransposition hallmarks, demonstrating how long-read sequencing can simultaneously survey the epigenome and detect somatic TE mobilization.

Splicing Kinetics and Coordination Revealed by Direct Nascent RNA Sequencing through Nanopores.

Understanding how splicing events are coordinated across numerous introns in metazoan RNA transcripts requires quantitative analyses of transient RNA processing events in living cells. We developed nanopore analysis of co-transcriptional processing (nano-COP), in which nascent RNAs are directly sequenced through nanopores, exposing the dynamics and patterns of RNA splicing without biases introduced by amplification. Long nano-COP reads reveal that, in human and Drosophila cells, splicing occurs after RNA polymerase II transcribes several kilobases of pre-mRNA, suggesting that metazoan splicing transpires distally from the transcription machinery. Inhibition of the branch-site recognition complex SF3B rapidly diminished global co-transcriptional splicing. We found that splicing order does not strictly follow the order of transcription and is associated with cis-acting elements, alternative splicing, and RNA-binding factors. Further, neighboring introns in human cells tend to be spliced concurrently, implying that splicing of these introns occurs cooperatively. Thus, nano-COP unveils the organizational complexity of RNA processing.

Nanopore tweezers show fractional-nucleotide translocation in sequence-dependent pausing by RNA polymerase.

RNA polymerases (RNAPs) carry out the first step in the central dogma of molecular biology by transcribing DNA into RNA. Despite their importance, much about how RNAPs work remains unclear, in part because the small (3.4 Angstrom) and fast (~40 ms/nt) steps during transcription were difficult to resolve. Here, we used high-resolution nanopore tweezers to observe the motion of single Escherichia coli RNAP molecules as it transcribes DNA ~1,000 times improved temporal resolution, resolving single-nucleotide and fractional-nucleotide steps of individual RNAPs at saturating nucleoside triphosphate concentrations. We analyzed RNAP during processive transcription elongation and sequence-dependent pausing at the yrbL elemental pause sequence. Each time RNAP encounters the yrbL elemental pause sequence, it rapidly interconverts between five translocational states, residing predominantly in a half-translocated state. The kinetics and force-dependence of this half-translocated state indicate it is a functional intermediate between pre- and post-translocated states. Using structural and kinetics data, we show that, in the half-translocated and post-translocated states, sequence-specific protein-DNA interaction occurs between RNAP and a guanine base at the downstream end of the transcription bubble (core recognition element). Kinetic data show that this interaction stabilizes the half-translocated and post-translocated states relative to the pre-translocated state. We develop a kinetic model for RNAP at the yrbL pause and discuss this in the context of key structural features.

Label-free and amplification-free viral RNA quantification from primate biofluids using a trapping-assisted optofluidic nanopore platform.

Viral outbreaks can cause widespread disruption, creating the need for diagnostic tools that provide high performance and sample versatility at the point of use with moderate complexity. Current gold standards such as PCR and rapid antigen tests fall short in one or more of these aspects. Here, we report a label-free and amplification-free nanopore sensor platform that overcomes these challenges via direct detection and quantification of viral RNA in clinical samples from a variety of biological fluids. The assay uses an optofluidic chip that combines optical waveguides with a fluidic channel and integrates a solid-state nanopore for sensing of individual biomolecules upon translocation through the pore. High specificity and low limit of detection are ensured by capturing RNA targets on microbeads and collecting them by optical trapping at the nanopore location where targets are released and rapidly detected. We use this device for longitudinal studies of the viral load progression for Zika and Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infections in marmoset and baboon animal models, respectively. The up to million-fold trapping-based target concentration enhancement enables amplification-free RNA quantification across the clinically relevant concentration range down to the assay limit of RT-qPCR as well as cases in which PCR failed. The assay operates across all relevant biofluids, including semen, urine, and whole blood for Zika and nasopharyngeal and throat swab, rectal swab, and bronchoalveolar lavage for SARS-CoV-2. The versatility, performance, simplicity, and potential for full microfluidic integration of the amplification-free nanopore assay points toward a unique approach to molecular diagnostics for nucleic acids, proteins, and other targets.

Genomics in the long-read sequencing era.

Long-read sequencing (LRS) technologies have provided extremely powerful tools to explore genomes. While in the early years these methods suffered technical limitations, they have recently made significant progress in terms of read length, throughput, and accuracy and bioinformatics tools have strongly improved. Here, we aim to review the current status of LRS technologies, the development of novel methods, and the impact on genomics research. We will explore the most impactful recent findings made possible by these technologies focusing on high-resolution sequencing of genomes and transcriptomes and the direct detection of DNA and RNA modifications. We will also discuss how LRS methods promise a more comprehensive understanding of human genetic variation, transcriptomics, and epigenetics for the coming years.

Beyond the exome: What's next in diagnostic testing for Mendelian conditions.

Despite advances in clinical genetic testing, including the introduction of exome sequencing (ES), more than 50% of individuals with a suspected Mendelian condition lack a precise molecular diagnosis. Clinical evaluation is increasingly undertaken by specialists outside of clinical genetics, often occurring in a tiered fashion and typically ending after ES. The current diagnostic rate reflects multiple factors, including technical limitations, incomplete understanding of variant pathogenicity, missing genotype-phenotype associations, complex gene-environment interactions, and reporting differences between clinical labs. Maintaining a clear understanding of the rapidly evolving landscape of diagnostic tests beyond ES, and their limitations, presents a challenge for non-genetics professionals. Newer tests, such as short-read genome or RNA sequencing, can be challenging to order, and emerging technologies, such as optical genome mapping and long-read DNA sequencing, are not available clinically. Furthermore, there is no clear guidance on the next best steps after inconclusive evaluation. Here, we review why a clinical genetic evaluation may be negative, discuss questions to be asked in this setting, and provide a framework for further investigation, including the advantages and disadvantages of new approaches that are nascent in the clinical sphere. We present a guide for the next best steps after inconclusive molecular testing based upon phenotype and prior evaluation, including when to consider referral to research consortia focused on elucidating the underlying cause of rare unsolved genetic disorders.

The functional impact of 1,570 individual amino acid substitutions in human OTC.

Deleterious mutations in the X-linked gene encoding ornithine transcarbamylase (OTC) cause the most common urea cycle disorder, OTC deficiency. This rare but highly actionable disease can present with severe neonatal onset in males or with later onset in either sex. Individuals with neonatal onset appear normal at birth but rapidly develop hyperammonemia, which can progress to cerebral edema, coma, and death, outcomes ameliorated by rapid diagnosis and treatment. Here, we develop a high-throughput functional assay for human OTC and individually measure the impact of 1,570 variants, 84% of all SNV-accessible missense mutations. Comparison to existing clinical significance calls, demonstrated that our assay distinguishes known benign from pathogenic variants and variants with neonatal onset from late-onset disease presentation. This functional stratification allowed us to identify score ranges corresponding to clinically relevant levels of impairment of OTC activity. Examining the results of our assay in the context of protein structure further allowed us to identify a 13 amino acid domain, the SMG loop, whose function appears to be required in human cells but not in yeast. Finally, inclusion of our data as PS3 evidence under the current ACMG guidelines, in a pilot reclassification of 34 variants with complete loss of activity, would change the classification of 22 from variants of unknown significance to clinically actionable likely pathogenic variants. These results illustrate how large-scale functional assays are especially powerful when applied to rare genetic diseases.

TERRA ONTseq: a long-read-based sequencing pipeline to study the human telomeric transcriptome.

The long noncoding RNA TERRA is transcribed from telomeres in virtually all eukaryotes with linear chromosomes. In humans, TERRA transcription is driven in part by promoters comprising CpG dinucleotide-rich repeats of 29 bp repeats, believed to be present in half of the subtelomeres. Thus far, TERRA expression has been analyzed mainly using molecular biology-based approaches that only generate partial and somehow biased results. Here, we present a novel experimental pipeline to study human TERRA based on long-read sequencing (TERRA ONTseq). By applying TERRA ONTseq to different cell lines, we show that the vast majority of human telomeres produce TERRA and that the cellular levels of TERRA transcripts vary according to their chromosomes of origin. Using TERRA ONTseq, we also identified regions containing TERRA transcription start sites (TSSs) in more than half of human subtelomeres. TERRA TSS regions are generally found immediately downstream from 29 bp repeat-related sequences, which appear to be more widespread than previously estimated. Finally, we isolated a novel TERRA promoter from the highly expressed subtelomere of the long arm of Chromosome 7. With the development of TERRA ONTseq, we provide a refined picture of human TERRA biogenesis and expression and we equip the scientific community with an invaluable tool for future studies.

DeepBAM: a high-accuracy single-molecule CpG methylation detection tool for Oxford nanopore sequencing.

Recent nanopore sequencing system (R10.4) has enhanced base calling accuracy and is being increasingly utilized for detecting CpG methylation state. However, the robustness and universality of the methylation calling model in officially supplied Dorado remains poorly tested. In this study, we obtained heterogeneous datasets from human and plant sources to carry out comprehensive evaluations, which showed that Dorado performed significantly different across datasets. We therefore developed deep neural networks and implemented several optimizations in training a new model called DeepBAM. DeepBAM achieved superior and more stable performances compared with Dorado, including higher area under the ROC curves (98.47% on average and up to 7.36% improvement) and F1 scores (94.97% on average and up to 16.24% improvement) across the datasets. DeepBAM-based whole genome methylation frequencies have achieved >0.95 correlations with BS-seq on four of five datasets, outperforming Dorado in all instances. It enables unraveling allele-specific methylation patterns, including regions of transposable elements. The enhanced performance of DeepBAM paves the way for broader applications of nanopore sequencing in CpG methylation studies.

Benchmarking of computational methods for m6A profiling with Nanopore direct RNA sequencing.

N6-methyladenosine (m6A) is the most abundant internal eukaryotic mRNA modification, and is involved in the regulation of various biological processes. Direct Nanopore sequencing of native RNA (dRNA-seq) emerged as a leading approach for its identification. Several software were published for m6A detection and there is a strong need for independent studies benchmarking their performance on data from different species, and against various reference datasets. Moreover, a computational workflow is needed to streamline the execution of tools whose installation and execution remains complicated. We developed NanOlympicsMod, a Nextflow pipeline exploiting containerized technology for comparing 14 tools for m6A detection on dRNA-seq data. NanOlympicsMod was tested on dRNA-seq data generated from in vitro (un)modified synthetic oligos. The m6A hits returned by each tool were compared to the m6A position known by design of the oligos. In addition, NanOlympicsMod was used on dRNA-seq datasets from wild-type and m6A-depleted yeast, mouse and human, and each tool's hits were compared to reference m6A sets generated by leading orthogonal methods. The performance of the tools markedly differed across datasets, and methods adopting different approaches showed different preferences in terms of precision and recall. Changing the stringency cut-offs allowed for tuning the precision-recall trade-off towards user preferences. Finally, we determined that precision and recall of tools are markedly influenced by sequencing depth, and that additional sequencing would likely reveal additional m6A sites. Thanks to the possibility of including novel tools, NanOlympicsMod will streamline the benchmarking of m6A detection tools on dRNA-seq data, improving future RNA modification characterization.

Real-time label-free detection of dynamic aptamer-small molecule interactions using a nanopore nucleic acid conformational sensor.

Nucleic acids can undergo conformational changes upon binding small molecules. These conformational changes can be exploited to develop new therapeutic strategies through control of gene expression or triggering of cellular responses and can also be used to develop sensors for small molecules such as neurotransmitters. Many analytical approaches can detect dynamic conformational change of nucleic acids, but they need labeling, are expensive, and have limited time resolution. The nanopore approach can provide a conformational snapshot for each nucleic acid molecule detected, but has not been reported to detect dynamic nucleic acid conformational change in response to small -molecule binding. Here we demonstrate a modular, label-free, nucleic acid-docked nanopore capable of revealing time-resolved, small molecule-induced, single nucleic acid molecule conformational transitions with millisecond resolution. By using the dopamine-, serotonin-, and theophylline-binding aptamers as testbeds, we found that these nucleic acids scaffolds can be noncovalently docked inside the MspA protein pore by a cluster of site-specific charged residues. This docking mechanism enables the ion current through the pore to characteristically vary as the aptamer undergoes conformational changes, resulting in a sequence of current fluctuations that report binding and release of single ligand molecules from the aptamer. This nanopore tool can quantify specific ligands such as neurotransmitters, elucidate nucleic acid-ligand interactions, and pinpoint the nucleic acid motifs for ligand binding, showing the potential for small molecule biosensing, drug discovery assayed via RNA and DNA conformational changes, and the design of artificial riboswitch effectors in synthetic biology.

Probing RNA structure and dynamics using nanopore and next generation sequencing.

It has become increasingly evident that the structures RNAs adopt are conformationally dynamic; the various structured states that RNAs sample govern their interactions with other nucleic acids, proteins, and ligands to regulate a myriad of biological processes. Although several biophysical approaches have been developed and used to study the dynamic landscape of structured RNAs, technical limitations have limited their application to all classes of RNA due to variable size and flexibility. Recent advances combining chemical probing experiments with next-generation- and direct sequencing have emerged as an alternative approach to exploring the conformational dynamics of RNA. In this review, we provide a methodological overview of the sequencing-based techniques used to study RNA conformational dynamics. We discuss how different techniques have enabled us to better understand the propensity of RNAs from a variety of different classes to sample multiple conformational states. Finally, we present examples of the ways these techniques have reshaped how we think about RNA structure.

A blood drop through the pore: nanopore sequencing in hematology.

The development of new sequencing platforms, technologies, and bioinformatics tools in the past decade fostered key discoveries in human genomics. Among the most recent sequencing technologies, nanopore sequencing (NS) has caught the interest of researchers for its intriguing potential and flexibility. This up-to-date review highlights the recent application of NS in the hematology field, focusing on progress and challenges of the technological approaches employed for the identification of pathologic alterations. The molecular and analytic pipelines developed for the analysis of the whole-genome, target regions, and transcriptomics provide a proof of evidence of the unparalleled amount of information that could be retrieved by an innovative approach based on long-read sequencing.

Beyond sequencing: machine learning algorithms extract biology hidden in Nanopore signal data.

Nanopore sequencing provides signal data corresponding to the nucleotide motifs sequenced. Through machine learning-based methods, these signals are translated into long-read sequences that overcome the read size limit of short-read sequencing. However, analyzing the raw nanopore signal data provides many more opportunities beyond just sequencing genomes and transcriptomes: algorithms that use machine learning approaches to extract biological information from these signals allow the detection of DNA and RNA modifications, the estimation of poly(A) tail length, and the prediction of RNA secondary structures. In this review, we discuss how developments in machine learning methodologies contributed to more accurate basecalling and lower error rates, and how these methods enable new biological discoveries. We argue that direct nanopore sequencing of DNA and RNA provides a new dimensionality for genomics experiments and highlight challenges and future directions for computational approaches to extract the additional information provided by nanopore signal data.

Replicon-seq: seeing is believing.

Claussin et al. introduce Replicon-seq, a new genome-wide DNA sequencing technology that monitors the progression of individual replisomes at high resolution in vivo.