Deciphering Neurodegenerative Diseases Using Long-Read Sequencing.

Somatic SVs significantly contribute to cancer development and progression. Characterizing these variations has traditionally been difficult due to the limitations of short-read sequencing technologies and the diverse types and lengths of SVs. The advent of long-read sequencing has enabled a more comprehensive analysis of germline SVs, highlighting its potential applications in cancer genomics. The melanoma cell line COLO829, along with its normal counterpart COLO829BL, is a standard reference for somatic SV detection. Valle-Inclan et al. recently validated 68 somatic SVs combining short-read, long-read, and linked-read sequencing data. However, the sensitivity may be compromised as only a limited number of alignment-based callers were employed, such as NanoSV, Sniffles (for Oxford Nanopore Technologies (ONT)), and pbsv for (PacBio HiFi). As more alignment-based SV callers are being developed, it is crucial to integrate a broader range of tools to construct a comprehensive call set of somatic SVs. Moreover, the performance of assembly-based methods in somatic SV detection within cancer remains largely unexplored. In this study, we aimed to establish a comprehensive spectrum of somatic SVs in the COLO829 melanoma cell line by employing both alignment-based and assembly-based methods with long-read whole-genome sequencing data from PacBio and ONT aligned with Minimap2, SVs were identified and integrated from 7 alignment-based callers: cuteSV, NanoVar, DeBreak, Sniffles2, Svision-Pro, NanoSV, and pbsv. In addition, genome assemblies were constructed via Hifiasm and Verkko, incorporating HiFi reads with Hi-C and ultra-long ONT integration, followed by SV detection using four assembly-based callers: Dipcall, PAV, SVIM-asm, and cuteSV. A dedicated pipeline was developed to identify and filter somatic SVs from germline events, which considers mapping quality, sequencing depth of SV regions and their flanking regions, and 50% reciprocal overlap. Compared to the truth set established by Valle-Inclan et al., we discovered 19 novel somatic SVs, including 10 deletions, 4 insertions, 3 duplications, and 2 inversions. As a comparison, assembly-based methods detected all the deletions, insertions and duplications found by the alignment-based methods. However, it missed 20 inversions and 6 translocations. Our findings highlight the superior sensitivity of alignment-based techniques in somatic SV detection and underscore the complementary nature of assembly-based approaches. This work enhances the benchmark for somatic SV characterization in cancer genomics and confirms the utility of integrated long-read sequencing analyses. Citation Format: Zishan Peng, Zechen Chong. Full spectrum of somatic structural variations (SVs) detection in COLO829 with long-read sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5056.

The last two decades have seen tremendous advancements in tools like CRISPR, single-molecule sequencing technologies, optical genome mapping, single-cell omics techniques, etc. Genomic analyses of multiple individuals become important to address medical questions and advances in genomic technologies and methods directly contribute to improved outcomes in disease research and healthcare. Genome-wide association studies conducted in the past inform us about the limitations of technologies in analyzing factors contributing to human traits and diseases using only short-read amplicon sequencing technologies, especially in repetitive genomic stretches where the likelihood of structural variations is higher. While short-read sequencing is a highly evolved technology, the discovery of causative variants with it alone is impeded by its read length and depending on the assay, is limited to gene coding regions, and less penetrative variants are often missed. In a recent report, it was found that only about one in three known genetic disorders in children have been diagnosed successfully with short-read sequencing (SRS, including whole exome and whole genome assays). On the other hand, building evidence that variants occurring in extragenic regions are found to be driving mutations for diseases shows that there is a need to capture both intergenic and extragenic information. Long-read platforms including optical genome mapping and Pacific Biosciences (PacBio) or Oxford Nanopore Technology (ONT) sequencers have advantages like improved contiguity, long-range haplotype phasing, and therefore, identification of structural variants associated with diseases, especially where alleles extend beyond typical read length. They are better suited to capture large structural variations, their genotypes, and copy number alterations but some practical challenges, like lack of base-level resolution for optical mapping, high error rates, cost per sample, low throughput, and resource-heavy informatics analysis for long-read sequencing, prevent routine adoption long-read platforms. Targeted interrogation of the genome in lieu of the whole genome alleviates some of the above challenges. CRISPR-Cas9-based targeting methods offer programmability and thus are being increasingly used for long-read platforms. This thesis discusses novel applications of CRISPR-Cas9 nickase-based experimental methods for targeted interrogation of genomic features on long-read sequencing and optical mapping platforms. First, the linked-pair sequencing strategy enabled by CRISPR-Cas9n chemistry is described. Here, orderly fragmentation of DNA molecules is performed using CRISPR-Cas9n and pairs of sgRNA in such a way that produced fragments share identical termini. This strategy is capable of greater multiplicity and can assemble critical genetic loci effectively. The validity and efficacy of the method for sequencing were first demonstrated on a lambda phage model and Haemophilus influenzae model, and later for sequencing a cancer panel in the human genome containing 100 full-length gene sequences. When the designed linker sequences contained heterozygous genetic variants, long haplotypes could be established. These whole-gene haplotypes enable the study of genetic variants at non-coding regulatory elements and the detection of any allele-specific effects. The use of Cas9n to introduce nicks allowed for preferential ligation of sequencing adapters resulting in significant enrichment of target regions. Second, multicolor whole genome labeling for optical mapping technique, enabled by CRISPR-Cas9n, is described. Here, Cas9n is used to make directed nicks at target sites to incorporate fluorophores. This technique was used in the detection and quantification of known biomarkers (telomeres and D4Z4 units) and in finding the locations of LINE-1 insertions across the genome With Cas9-mediated nick-labeling, it is possible to target and fluorescently label any 20mer or the combination of multiple 20mers across the whole genome, especially in repetitive regions lacking DLE motifs. Custom maps can be generated to enable precise detection of breakpoints and interrogate the repetitive sequences; this enables more in-depth analysis of SVs than was previously possible. Application of this method in the interrogation of exogenic DNA integrations in the host genome for gene therapy validation and safety assessment is also demonstrated. Finally, additional applications of Cas9n chemistry using both long-read sequencing and optical genome mapping platforms together are demonstrated. Multicolor Cas9n-mediated labeling chemistry is leveraged to create high-density optical maps with an increased resolution for use in structural variant analysis, calling breakpoints, and scaffolding genome assemblies. Such high-density optical maps can also be used to study interactions of Cas9 with target DNA.

Obtaining a precise molecular diagnosis through clinical genetic testing provides information about disease prognosis or progression, allows accurate counseling about recurrence risk, and empowers individuals to benefit from precision therapies or take part in N-of-1 trials. Unfortunately, more than half of individuals with a suspected Mendelian condition remain undiagnosed after a comprehensive clinical evaluation, and the results of any individual clinical genetic test ordered during a typical evaluation may take weeks or months to return. Furthermore, commonly used technologies, such as short-read sequencing, are limited in the types of disease-causing variation they can identify. New technologies, such as long-read sequencing (LRS), are poised to solve these problems. Recent technical advances have improved accuracy, increased throughput, and decreased the costs of commercially available LRS technologies. This has resolved many historical concerns about the use of LRS in the clinical environment and opened the door to widespread clinical adoption of LRS. Here, we review LRS technology, how it has been used in the research setting to clarify complex variants or identify disease-causing variation missed by prior clinical testing, and how it may be used clinically in the near future. LRS is unique in that, as a single data source, it has the potential to replace nearly every other clinical genetic test offered today. When analyzed in a stepwise fashion, LRS will simplify laboratory processes, reduce barriers to comprehensive genetic testing, increase the rate of genetic diagnoses, and shorten the amount of time required to make a molecular diagnosis.

BackgroundThe barred knifejaw (Oplegnathus fasciatus), a member of the Oplegnathidae family of the Centrarchiformes, is a commercially important rocky reef fish native to East Asia. Oplegnathus fasciatus has become an important fishery resource for offshore cage aquaculture and fish stocking of marine ranching in China, Japan, and Korea. Recently, sexual dimorphism in growth with neo-sex chromosome and widespread biotic diseases in O. fasciatus have been increasing concern in the industry. However, adequate genome resources for gaining insight into sex-determining mechanisms and establishing genetically resistant breeding systems for O. fasciatus are lacking. Here, we analyzed the entire genome of a female O. fasciatus fish using long-read sequencing and Hi-C data to generate chromosome-length scaffolds and a highly contiguous genome assembly.FindingsWe assembled the O. fasciatus genome with a total of 245.0 Gb of raw reads that were generated using both Pacific Bioscience (PacBio) Sequel and Illumina HiSeq 2000 platforms. The final draft genome assembly was approximately 778.7 Mb, which reached a high level of continuity with a contig N50 of 2.1 Mb. The genome size was consistent with the estimated genome size (777.5 Mb) based on k-mer analysis. We combined Hi-C data with a draft genome assembly to generate chromosome-length scaffolds. Twenty-four scaffolds corresponding to the 24 chromosomes were assembled to a final size of 768.8 Mb with a contig N50 of 2.1 Mb and a scaffold N50 of 33.5 Mb using 1,372 contigs. The identified repeat sequences accounted for 33.9% of the entire genome, and 24 003 protein-coding genes with an average of 10.1 exons per gene were annotated using de novo methods, with RNA sequencing data and homologies to other teleosts. According to phylogenetic analysis using protein-coding genes, O. fasciatus is closely related to Larimichthys crocea, with O. fasciatus diverging from their common ancestor approximately 70.5–88.5 million years ago.ConclusionsWe generated a high-quality draft genome for O. fasciatus using long-read PacBio sequencing technology, which represents the first chromosome-level reference genome for Oplegnathidae species. Assembly of this genome assists research into fish sex-determining mechanisms and can serve as a resource for accelerating genome-assisted improvements in resistant breeding systems.

Apple replant disease (ARD) has been observed to cause 50% mortality in fields where apples are replanted, which has seriously limited the sustainable development of China's apple industry. Our previous study revealed that Fusarium oxysporum is one of the causal agents of ARD; however, its pathogenic mechanism is still unclear. In this study, we obtained the draft genome of Fusarium oxysporum f. sp. malus HS2 using a combination of long-read single-molecule real-time sequencing technology (Pacific Biosciences [PacBio]) and MGISEQ sequencing. The total length of the assembled was 56,825,273 bp, and the GC content was 47.72%. The genome provides a valuable resource for facilitating our understanding the response of F. oxysporum to apple. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

The advent of long-read (LR) sequencing technologies has provided a direct opportunity to determine the structure of transcripts with potential for end-to-end sequencing of full-length RNAs. LR methods that have been described to date include commercial offerings from Oxford Nanopore Technologies (ONT) and Pacific Biosciences. These kits are based on selection of polyadenylated (polyA+) RNAs and/or oligo-dT priming of reverse transcription. Thus, these approaches do not allow comprehensive interrogation of the transcriptome due to their exclusion of non-polyadenylated (polyA-) RNAs. In addition, polyA + specificity also results in 3'-biased measurements of PolyA+ RNAs especially when the RNA input is partially degraded. To address these limitations of current LR protocols, we modified rRNA depletion protocols that have been used in short-read sequencing: one approach representing a ligation-based method and the other a template-switch cDNA synthesis-based method to append ONT-specific adaptor sequences and by removing any deliberate fragmentation/shearing of RNA/cDNA. Here, we present comparisons with poly+ RNA-specific versions of the two approaches including the ONT PCR-cDNA Barcoding kit. The rRNA depletion protocols displayed higher proportions (30%-50%) of intronic content compared to that of the polyA-specific protocols (5%-8%). In addition, the rRNA depletion protocols enabled ∼20-50% higher detection of expressed genes. Other metrics that were favourable to the rRNA depletion protocols include better coverage of long transcripts, and higher accuracy and reproducibility of expression measurements. Overall, these results indicate that the rRNA depletion-based protocols described here allow the comprehensive characterization of polyadenylated and non-polyadenylated RNAs. While the resulting reads are long enough to help decipher transcript structures, future endeavors are warranted to improve the proportion of individual reads representing end-to-end spanning of transcripts.

Introduction: Accurate detection and prioritization of tumor-specific somatic variants is foundational to the development of personalized immunotherapies. Traditional pipelines for neoepitope identification rely heavily on short-read next-generation sequencing (NGS) and DNA-based variant calling, followed by RNA expression filtering and HLA-binding prediction. However, this approach is limited by time-intensive workflows, potential false positives from DNA-only calls, and poor capture of complex isoforms or RNA-level editing. Moreover, the accuracy of neoepitope prediction is constrained by conventional sequence-based HLA binding algorithms that do not account for structural and biophysical features of peptide-MHC interactions, particularly across underrepresented HLA alleles. Methods: To overcome these limitations, we developed a streamlined, sequencing-to-vaccine framework that leverages long-read RNA sequencing for direct detection of expressed somatic variants, including fusions, indels, and single nucleotide variants. Using Oxford Nanopore Technologies’ cDNA-PCR approach, we enable comprehensive, full-length transcript characterization from both fresh and frozen breast tumor samples. Our bioinformatic pipeline, NeoTarget, integrates alignment, variant calling, and neoepitope inference from tumor RNA in a single, modular workflow. A core innovation of this pipeline is HLA-Inception, a deep convolutional neural network trained to predict peptide-MHC class I binding using features derived from molecular dynamics-based modeling of electrostatic potential at the peptide-HLA interface, enhancing generalizability across diverse HLA subtypes. Results: Expanding on previous results, the current NeoTarget pipeline identifies, evaluates, and prioritizes single nucleotide variants, indels, and fusions. To validate this system, we used a set of 9 human breast cancer tumors benchmarked with short read sequencing. Identified neoantigens included most variants shown by clinical short read sequencing and also novel structural variants (i.e., fusions) only revealed with long read sequencing with high confidence. Conclusion: Here, we describe the design and performance of the NeoTarget pipeline, and show proof-of-concept feasibility of applying this fast and cost-effective workflow for HLA-restricted epitope discovery in breast tumors using long-read RNA sequencing. Overall, these methods can be applied to rapidly identify and prioritize neoantigens for personalized neoantigen-based immune therapies. Citation Format: F. Batalini, S. Henry, Y. Zhang, R. Foster, J. M. Gayton, A. Hostal, E. A. Wilson, A. Singharoy, M. Gustafson, B. Pockaj, J. Park, K. S. Anderson. Somatic variant detection using long read RNA sequencing reveals HLA-restricted targets for immunotherapy [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS3-06-08.

Structural variation (SV) is typically defined as variation within the human genome that exceeds 50 base pairs (bp). SV may be copy number neutral or it may involve duplications, deletions, and complex rearrangements. Recent studies have shown SV to be associated with many human diseases. However, studies of SV have been challenging due to technological constraints. With the advent of third generation (long-read) sequencing technology, exploration of longer stretches of DNA not easily examined previously has been made possible. In the present study, we utilized third generation (long-read) sequencing techniques to examine SV in the EGFR landscape of four haplotypes derived from two human samples. We analyzed the EGFR gene and its landscape (+/- 500,000 base pairs) using this approach and were able to identify a region of non-coding DNA with over 90% similarity to the most common activating EGFR mutation in non-small cell lung cancer. Based on previously published Alu-element genome instability algorithms, we propose a molecular mechanism to explain how this non-coding region of DNA may be interacting with and impacting the stability of the EGFR gene and potentially generating this cancer-driver gene. By these techniques, we were also able to identify previously hidden structural variation in the four haplotypes and in the human reference genome (hg38). We applied previously published algorithms to compare the relative stabilities of these five different EGFR gene landscape haplotypes to estimate their relative potentials to generate the EGFR exon 19, 15 bp canonical deletion. To our knowledge, the present study is the first to use the differences in genomic architecture between targeted cancer-linked phased haplotypes to estimate their relative potentials to form a common cancer-linked driver mutation.

Long-read sequencing is currently supported by sequencing platforms from Pacific Biosciences and Oxford Nanopore Technologies, both of which generate ultra-long reads. Metabarcoding and metagenomics are the two approaches used when implementing sequencing. Metabarcoding involves the amplification and sequencing of selected nucleic acid regions, while in a metagenomic approach extracted nucleic acids are sequenced directly without prior amplification. Both approaches have associated advantages and disadvantages, which, in combination with long-read sequencing, provide a promising new approach for fungal identification and diagnosis of mycoses, on which we will reflect in this short review.

ObjectivesDevelopment of sequencing technology has opened up vast opportunities for tree genomic research in the tropics. One of the aforesaid technologies named ONT (Oxford Nanopore Technology) has attracted researchers in undertaking testings and experiments due to its affordability and accessibility. To the best of our knowledge, there has been no published reports on the use of ONT for genomic analysis of Indonesian tree species. This progress is promising for further improvement in order to acquire more genomic data for research purposes. Therefore, the present study was carried out to determine the effectiveness of ONT in generating long-read DNA sequences using DNA isolated from leaves and wood cores of Macassar ebony (Diospyros celebica Bakh.).Data descriptionLong-read sequences data of leaves and wood cores of Macassar ebony were generated by using the MinION device and MinKnow v3.6.5 (ONT). The obtained data, as the first long-read sequence dataset for Macassar ebony, is of great importance to conserve the genetic diversity, understanding the molecular mechanism, and sustainable use of plant genetic resources for downstream applications.

The link between viruses and cancer has intrigued scientists for decades. Certain viruses have been shown to be vital in the development of various cancers by integrating viral DNA into the host genome and activating viral oncogenes. These viruses include the Human Papillomavirus (HPV), Hepatitis B and C Viruses (HBV and HCV), Epstein-Barr Virus (EBV), and Human T-Cell Leukemia Virus (HTLV-1), which are all linked to the development of a myriad of human cancers. Third-generation sequencing technologies have revolutionized our ability to study viral integration events at unprecedented resolution in recent years. They offer long sequencing capabilities along with the ability to map viral integration sites, assess host gene expression, and track clonal evolution in cancer cells. Recently, researchers have been exploring the application of Oxford Nanopore Technologies (ONT) nanopore sequencing and Pacific BioSciences (PacBio) single-molecule real-time (SMRT) sequencing in cancer research. As viral integration is crucial to the development of cancer via viruses, third-generation sequencing would provide a novel approach to studying the relationship interlinking viral oncogenes, viruses, and cancer. This review article explores the molecular mechanisms underlying viral oncogenesis, the role of viruses in cancer development, and the impact of third-generation sequencing on our understanding of viral integration into the human genome.

Amplifying long and complex genomic regions with high fidelity is essential for accurate long-read sequencing, especially in diseases linked to repeat expansions, where polymerase slippage and stalling can compromise sequencing results, ultimately impacting disease diagnosis and prognosis. In Fragile X Syndrome, for example, amplifying the FMR1 gene is challenging due to CGG repeat expansions that often exceed 200 repeats. Also, Short-read Next Generation Sequencing struggles to detect these expansions accurately, relying on computational algorithms for sequence assembly, this can reduce sequence and, therefore, diagnostic accuracy. Consequently, long-read sequencing offers a more reliable method for directly identifying longer sequences, with the amplification step being crucial to ensuring successful detection. We evaluated the performance of DeCodi-Fi, a novel high-fidelity polymerase, by amplifying and sequencing genes with tandem repeats linked with the following disease-associated genes: FMR1 (Fragile X Syndrome), C9orf72 (Amyotrophic Lateral Sclerosis, ALS), IT15 (Huntington*s Disease), and X25 (Friedreich*s Ataxia), as well as long templates exceeding 12 kb, including BRCA1 (Breast Cancer) and SMN1 (Spinal Muscular Atrophy) in previously reported healthy and diagnosed individuals. Sequencing analysis was performed to assess DeCodi-Fi*s accuracy and ability to amplify complex templates without introducing errors. Its performance was also compared against other commercial high-fidelity polymerase. We successfully optimized PCR conditions for four repeat expansion targets and two long amplicons of clinical relevance. Long-read sequencing libraries were generated and analyzed using Oxford Nanopore technology. Consensus sequences were mapped to curated data from the corresponding Coriell samples. DeCodi-Fi polymerase successfully amplified repeat expansions with +/- 1 repeat accuracy. For the non-repeated long amplicons we obtained full coverage and polymerase error rates below the sequencing error threshold, when compared to the repository sequence data. This study demonstrates that DeCodi-Fi is capable of amplifying complex and long DNA templates with minimal errors, providing a reliable tool for long-read sequencing involving challenging genomic regions.

Alternative splicing is an essential mechanism for generating protein diversity by producing distinct isoforms from a single gene. Dysregulation of splicing that affects pancreatic function and immune tolerance has been linked to both types 1 and 2 diabetes. Next-generation sequencing technologies, with their short read lengths, are limited in their ability to accurately detect splice variants. Long-read sequencing technologies offer the potential to overcome these limitations by providing full-length transcript information; however, their application in single-cell RNA sequencing has been hindered by technical challenges, including insufficient read lengths and higher error rates. Furthermore, cell types that produce high levels of a single transcript, such as islet endocrine cells, can obscure identification of lower-abundance transcripts. In this study, we optimized a protocol for single-cell long-read sequencing in pancreatic islets to improve read length and transcript detection. Our findings demonstrate that 5′ library preparation protocols outperform 3′ protocols, resulting in better transcript identification. Furthermore, we show that targeted depletion of insulin transcripts enhances the detection of informative reads, highlighting the utility of transcript-depletion strategies. This optimized protocol enables isoform-specific gene expression analysis and reveals differential transcript usage across the various cell types in pancreatic islets. By leveraging this approach, we gain deeper insights into the transcriptomic complexity and cellular heterogeneity within pancreatic islets.Article HighlightsThis study addresses the limitations of current single-cell long-read RNA sequencing technologies in detecting full-length transcripts and isoform diversity, particularly in pancreatic islets.We demonstrate that optimizing single-cell library preparation protocols reproducibly enhances read length and transcript identification in pancreatic islets.Combined with targeted insulin depletion and extended reverse transcription, 5′ capture methods significantly improved read length and isoform detection compared with standard protocols, while maximizing the number of informative reads.These improvements yield longer reads in single-cell experiments, substantially enhancing transcript identification and enabling more accurate analysis of isoform diversity.

Aberrant splicing underlies many human diseases, including cancer, cardiovascular diseases and neurological disorders. Genome-wide mapping of splicing quantitative trait loci (sQTLs) has shown that genetic regulation of alternative splicing is widespread. However, identification of the corresponding isoform or protein products associated with disease-associated sQTLs is challenging with short-read RNA-seq, which cannot precisely characterize full-length transcript isoforms. Furthermore, contemporary sQTL interpretation often relies on reference transcript annotations, which are incomplete. Solutions to these issues may be found through integration of newly emerging long-read sequencing technologies. Long-read sequencing offers the capability to sequence full-length mRNA transcripts and, in some cases, to link sQTLs to transcript isoforms containing disease-relevant protein alterations. Here, we provide an overview of sQTL mapping approaches, the use of long-read sequencing to characterize sQTL effects on isoforms, the linkage of RNA isoforms to protein-level functions and comment on future directions in the field. Based on recent progress, long-read RNA sequencing promises to be part of the human disease genetics toolkit to discover and treat protein isoforms causing rare and complex diseases.

A comprehensive annotation of transcript isoforms in domesticated species is lacking. Especially considering that transcriptome complexity and splicing patterns are not well-conserved between species, this presents a substantial obstacle to genomic selection programs that seek to improve production, disease resistance, and reproduction. Recent advances in long-read sequencing technology have made it possible to directly extrapolate the structure of full-length transcripts without the need for transcript reconstruction. In this study, we demonstrate the power of long-read sequencing for transcriptome annotation by coupling Oxford Nanopore Technology (ONT) with large-scale multiplexing of 93 samples, comprising 32 tissues collected from adult male and female Hereford cattle. More than 30 million uniquely mapping full-length reads were obtained from a single ONT flow cell, and used to identify and characterize the expression dynamics of 99,044 transcript isoforms at 31,824 loci. Of these predicted transcripts, 21% exactly matched a reference transcript, and 61% were novel isoforms of reference genes, substantially increasing the ratio of transcript variants per gene, and suggesting that the complexity of the bovine transcriptome is comparable to that in humans. Over 7,000 transcript isoforms were extremely tissue-specific, and 61% of these were attributed to testis, which exhibited the most complex transcriptome of all interrogated tissues. Despite profiling over 30 tissues, transcription was only detected at about 60% of reference loci. Consequently, additional studies will be necessary to continue characterizing the bovine transcriptome in additional cell types, developmental stages, and physiological conditions. However, by here demonstrating the power of ONT sequencing coupled with large-scale multiplexing, the task of exhaustively annotating the bovine transcriptome – or any mammalian transcriptome – appears significantly more feasible.