High throughput cDNA sequencing technologies have advanced our understanding of transcriptome complexity and regulation. However, these methods lose information contained in biological RNA because the copied reads are often short and because modifications are not retained. We address these limitations using a native poly(A) RNA sequencing strategy developed by Oxford Nanopore Technologies (ONT). Our study generated 9.9 million aligned sequence reads for the human cell line GM12878, using thirty MinION flow cells at six institutions. These native RNA reads had a median length of 771 bases, and a maximum aligned length of over 21,000 bases. Mitochondrial poly(A) reads provided an internal measure of read length quality. We combined these long nanopore reads with higher accuracy short-reads and annotated GM12878 promoter regions, to identify 33,984 plausible RNA isoforms. We describe strategies for assessing 3′ poly(A) tail length, base modifications, and transcript haplotypes.

High throughput cDNA sequencing technologies have dramatically advanced our understanding of transcriptome complexity and regulation. However, these methods lose information contained in biological RNA because the copied reads are often short and because modifications are not carried forward in cDNA. We address these limitations using a native poly(A) RNA sequencing strategy developed by Oxford Nanopore Technologies (ONT). Our study focused on poly(A) RNA from the human cell line GM12878, generating 9.9 million aligned sequence reads. These native RNA reads had an aligned N50 length of 1294 bases, and a maximum aligned length of over 21,000 bases. A total of 78,199 high-confidence isoforms were identified by combining long nanopore reads with short higher accuracy Illumina reads. We describe strategies for assessing 3′ poly(A) tail length, base modifications and transcript haplotypes from nanopore RNA data. Together, these nanopore-based techniques are poised to deliver new insights into RNA biology.

Probing epigenetic features on DNA has tremendous potential to advance our understanding of the phased epigenome. In this study, we use nanopore sequencing to evaluate CpG methylation and chromatin accessibility simultaneously on long strands of DNA by applying GpC methyltransferase to exogenously label open chromatin. We performed nanopore sequencing of Nucleosome Occupancy and Methylome (nanoNOMe) on four human cell lines (GM12878, MCF-10A, MCF-7, MDA-MB-231). The single-molecule resolution allows footprinting of protein and nucleosome binding and determining the combinatorial promoter epigenetic signature on individual molecules. Long-read sequencing makes it possible to robustly assign reads to haplotypes, allowing us to generate the first fully phased human epigenome, consisting of chromosome-level allele-specific profiles of CpG methylation and chromatin accessibility. We further apply this to a breast cancer model to evaluate differential methylation and accessibility between cancerous and non-cancerous cells.

Current transcriptome annotations have largely relied on short read lengths intrinsic to the most widely used high-throughput cDNA sequencing technologies. For example, in the annotation of the Caenorhabditis elegans transcriptome, more than half of the transcript isoforms lack full-length support and instead rely on inference from short reads that do not span the full length of the isoform. We applied nanopore-based direct RNA sequencing to characterize the developmental polyadenylated transcriptome of C. elegans. Taking advantage of long reads spanning the full length of mRNA transcripts, we provide support for 23,865 splice isoforms across 14,611 genes, without the need for computational reconstruction of gene models. Of the isoforms identified, 3452 are novel splice isoforms not present in the WormBase WS265 annotation. Furthermore, we identified 16,342 isoforms in the 3 ′ untranslated region (3 ′ UTR), 2640 of which are novel and do not fall within 10 bp of existing 3 ′-UTR data sets and annotations. Combining 3 ′ UTRs and splice isoforms, we identified 28,858 fulllength transcript isoforms. We also determined that poly(A) tail lengths of transcripts vary across development, as do the strengths of previously reported correlations between poly(A) tail length and expression level, and poly(A) tail length and 3 ′-UTR length. Finally, we have formatted this data as a publicly accessible track hub, enabling researchers to explore this data set easily in a genome browser.

evolution of the virus but also the fundamental mechanisms by which control measures affected its epidemic spread. These efforts complement the information provided by the rapidly growing public databases of SARS-CoV-2 sequences by focusing the collection of genomic data in settings where we can access extensive current and past clinical data to investigate fundamental questions about this evolving virus's changing relationship with human health. MethodsData availability. Raw nanopore and Illumina data are deposited at SRA (BioProject PRJNA629390). Consensus sequences are deposited at GISAID and Genbank (MT509452-MT509493, and MT646048-MT646120) under BioProject PRJNA650037 (accession numbers available in Supplemental Table 3).Specimens and patient data. Clinical specimens used for genetic characterization were remnant nasopharyngeal swabs available at the completion of standard of care testing at the Johns Hopkins Hospital clinical virology laboratory. In total, 143 samples were selected for analysis based on their distribution throughout March 2020 and representation of the range of disease severity observed during this period. During this period, automated patient metadata extraction was limited to the date a sample was confirmed positive; all other data required patient chart reviews. Samples were sequenced in 2 phases, with the first phase enriched for patients admitted to the ICU (14 of 55 samples collected March 11-21), and the second a convenience sample that captured as many samples as possible for sequencing, irrespective of disease severity or ICU admission (10 of 88 samples collected March 13 -31).Clinical data analysis. Data including patient demographics, symptoms, comorbidities, COVID-19 exposure, recent travel history, and results of chest imaging at presentation were abstracted from the electronic medical record (EMR). COVID-19 treatment (medication, supplemental oxygen, and invasive mechanical ventilation) and outcomes (home observation without inpatient admission, discharge after admission, ongoing admission, and death) were also abstracted from the EMR. Race as self-reported by the patient and documented in the EMR was collected in prespecified categories. Patients who reported (a) contact with an individual known to be COVID-19-infected or (b) high-risk exposure (e.g., healthcare worker) were classified as COVID-19-exposed. Comorbidities were assessed based on diagnoses in the EMR (i.e., diabetes, obesity, or alcohol use disorder) and further categorized for lung disease (e.g., asthma, COPD), cardiac disease (e.g., valvular heart disease, arrhythmias, hypertension), and immunocompromised (e.g., HIV positive, hematologic malignancy, solid organ transplant).Nucleic acid extraction. Automated nucleic acid extraction was performed using either the NucliSENS easy-Mag or eMAG instruments (bioMérieux) using software version 2.1.0.1. easyMag or eMAG lysis buffer (2 mL) was added to 500 μL of aliquoted viral transport media in a biosafety cabinet in either a BSL-3 or BSL-2 facility using BSL-3 biosafe...