NanoSplicer: Accurate identification of splice junctions using Oxford Nanopore sequencing

Uncalled4 improves nanopore DNA and RNA modification detection via fast and accurate signal alignment

Nanopore signal analysis enables detection of nucleotide modifications from native DNA and RNA sequencing, providing both accurate genetic or transcriptomic and epigenetic information without additional library preparation. At present, only a limited set of modifications can be directly basecalled (for example, 5-methylcytosine), while most others require exploratory methods that often begin with alignment of nanopore signal to a nucleotide reference. We present Uncalled4, a toolkit for nanopore signal alignment, analysis and visualization. Uncalled4 features an efficient banded signal alignment algorithm, BAM signal alignment file format, statistics for comparing signal alignment methods and a reproducible de novo training method for k-mer-based pore models, revealing potential errors in Oxford Nanopore Technologies' state-of-the-art DNA model. We apply Uncalled4 to RNA 6-methyladenine (m6A) detection in seven human cell lines, identifying 26% more modifications than Nanopolish using m6Anet, including in several genes where m6A has known implications in cancer. Uncalled4 is available open source at github.com/skovaka/uncalled4 .

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

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

The promising role of nanopore sequencing in cancer diagnostics and treatment

Cancer arises from genetic alterations that impact both the genome and transcriptome. The utilization of nanopore sequencing offers a powerful means of detecting these alterations due to its unique capacity for long single-molecule sequencing. In the context of DNA analysis, nanopore sequencing excels in identifying structural variations (SVs), copy number variations (CNVs), gene fusions within SVs, and mutations in specific genes, including those involving DNA modifications and DNA adducts. In the field of RNA research, nanopore sequencing proves invaluable in discerning differentially expressed transcripts, uncovering novel elements linked to transcriptional regulation, and identifying alternative splicing events and RNA modifications at the single-molecule level. Furthermore, nanopore sequencing extends its reach to detecting microorganisms, encompassing bacteria and viruses, that are intricately associated with tumorigenesis and the development of cancer. Consequently, the application prospects of nanopore sequencing in tumor diagnosis and personalized treatment are expansive, encompassing tasks such as tumor identification and classification, the tailoring of treatment strategies, and the screening of prospective patients. In essence, this technology stands poised to unearth novel mechanisms underlying tumorigenesis while providing dependable support for the diagnosis and treatment of cancer.

Retinal Dystrophy Associated with Homozygous Variants in NRL

Background/Objectives: Neural retina leucine zipper (NRL) is a transcription factor involved in the differentiation of rod photoreceptors. Pathogenic variants in the gene encoding NRL have been associated with autosomal dominant retinitis pigmentosa and autosomal recessive clumped pigmentary retinal degeneration. Only a dozen unrelated families affected by recessive NRL-related retinal dystrophy have been described. The purpose of this study was to expand the genotypic spectrum of this disease by reporting clinical and genetic findings of two unrelated families. Methods: Index patients affected by retinal dystrophy were genetically tested by whole-exome sequencing (WES) and whole-genome sequencing (WGS). Segregation analysis within the families was performed for candidate variants. A minigene assay was performed to functionally characterize a variant suspected to affect splicing. Results: Variant filtering revealed homozygous NRL variants in both families. The variant in patient A was a small deletion encompassing the donor splice site of exon 1 of transcript NM_006177.3. The minigene assay revealed that this variant led to two aberrant transcripts that used alternative cryptic donor splice sites located in intron 1. In patient B, a stop-gain variant was identified in the last exon of NRL in a homozygous state due to maternal uniparental disomy of chromosome 14. Conclusions: Our study expands the genotypic spectrum of autosomal recessive NRL-related retinal dystrophy. Moreover, it underscores the importance of actively maintaining bioinformatic pipelines for variant detection and the utility of minigene assays in functionally characterizing candidate splicing variants.

Nanopore Deep Sequencing as a Tool to Characterize and Quantify Aberrant Splicing Caused by Variants in Inherited Retinal Dystrophy Genes

The contribution of splicing variants to molecular diagnostics of inherited diseases is reported to be less than 10%. This figure is likely an underestimation due to several factors including difficulty in predicting the effect of such variants, the need for functional assays, and the inability to detect them (depending on their locations and the sequencing technology used). The aim of this study was to assess the utility of Nanopore sequencing in characterizing and quantifying aberrant splicing events. For this purpose, we selected 19 candidate splicing variants that were identified in patients affected by inherited retinal dystrophies. Several in silico tools were deployed to predict the nature and estimate the magnitude of variant-induced aberrant splicing events. Minigene assay or whole blood-derived cDNA was used to functionally characterize the variants. PCR amplification of minigene-specific cDNA or the target gene in blood cDNA, combined with Nanopore sequencing, was used to identify the resulting transcripts. Thirteen out of nineteen variants caused aberrant splicing events, including cryptic splice site activation, exon skipping, pseudoexon inclusion, or a combination of these. Nanopore sequencing allowed for the identification of full-length transcripts and their precise quantification, which were often in accord with in silico predictions. The method detected reliably low-abundant transcripts, which would not be detected by conventional strategies, such as RT-PCR followed by Sanger sequencing.

Uncalled4 improves nanopore DNA and RNA modification detection via fast and accurate signal alignment

Nanopore signal analysis enables detection of nucleotide modifications from native DNA and RNA sequencing, providing both accurate genetic/transcriptomic and epigenetic information without additional library preparation. Presently, only a limited set of modifications can be directly basecalled (e.g. 5-methylcytosine), while most others require exploratory methods that often begin with alignment of nanopore signal to a nucleotide reference. We present Uncalled4, a toolkit for nanopore signal alignment, analysis, and visualization. Uncalled4 features an efficient banded signal alignment algorithm, BAM signal alignment file format, statistics for comparing signal alignment methods, and a reproducible de novo training method for k-mer-based pore models, revealing potential errors in ONT's state-of-the-art DNA model. We apply Uncalled4 to RNA 6-methyladenine (m6A) detection in seven human cell lines, identifying 26% more modifications than Nanopolish using m6Anet, including in several genes where m6A has known implications in cancer. Uncalled4 is available open-source at github.com/skovaka/uncalled4.

Oxford Nanopore Technology and its Application in Liquid Biopsies

Advanced medical technologies are transforming the future of healthcare, in particular, the screening and detection of molecular-genetic changes in patients suspected of having a neoplasm. They are based on the assumption that neoplasms release small amounts  of  various  neoplasm-specific molecules, such as tumor DNA, called circulating DNA (cirDNA), into the extracellular space and subsequently into the blood. The detection of tumor-specific molecules and specific molecular changes in body fluids in a noninvasive or minimally invasive approach is known as "liquid biopsy." The aim of this review is to summarize the current knowledge of the application of ONT for analyzing circulating DNA in the field of liquid biopsies among cancer patients. Databases were searched using the keywords "nanopore" and "liquid biopsy" and by applying strict inclusion criteria. This technique can be used for the detection of neoplastic disease, including metastases, guiding precision therapy, and monitoring its effects. There are many challenges, however, for the successful implementation of this technology into the clinical practice. The first one is the low amount of tumor-specific molecules in the body fluids. Secondly, a tumor molecular signature should be discriminated from benign conditions like clonal hematopoiesis of unknown significance. Oxford Nanopore Technology (ONT) is a third-generation sequencing technology that seems particularly promising to complete these tasks. It offers rapid sequencing thanks to its ability to detect changes in the density of the electric current passing through nanopores. Even though ONT still needs validation technology, it is a promising approach for early diagnosis, therapy guidance, and monitoring of different neoplasms based on analyzing the cirDNA.

Nanopore sequencing technology and its applications

Since the development of Sanger sequencing in 1977, sequencing technology has played a pivotal role in molecular biology research by enabling the interpretation of biological genetic codes. Today, nanopore sequencing is one of the leading third-generation sequencing technologies. With its long reads, portability, and low cost, nanopore sequencing is widely used in various scientific fields including epidemic prevention and control, disease diagnosis, and animal and plant breeding. Despite initial concerns about high error rates, continuous innovation in sequencing platforms and algorithm analysis technology has effectively addressed its accuracy. During the coronavirus disease (COVID-19) pandemic, nanopore sequencing played a critical role in detecting the severe acute respiratory syndrome coronavirus-2 virus genome and containing the pandemic. However, a lack of understanding of this technology may limit its popularization and application. Nanopore sequencing is poised to become the mainstream choice for preventing and controlling COVID-19 and future epidemics while creating value in other fields such as oncology and botany. This work introduces the contributions of nanopore sequencing during the COVID-19 pandemic to promote public understanding and its use in emerging outbreaks worldwide. We discuss its application in microbial detection, cancer genomes, and plant genomes and summarize strategies to improve its accuracy.

Single-cell and long-read sequencing to enhance modelling of splicing and cell-fate determination

Single-cell sequencing technologies have revolutionised the life sciences and biomedical research. Single-cell sequencing provides high-resolution data on cell heterogeneity, allowing high-fidelity cell type identification, and lineage tracking. Computational algorithms and mathematical models have been developed to make sense of the data, compensate for errors and simulate the biological processes, which has led to breakthroughs in our understanding of cell differentiation, cell-fate determination and tissue cell composition. The development of long-read (a.k.a. third-generation) sequencing technologies has produced powerful tools for investigating alternative splicing, isoform expression (at the RNA level), genome assembly and the detection of complex structural variants (at the DNA level). In this review, we provide an overview of the recent advancements in single-cell and long-read sequencing technologies, with a particular focus on the computational algorithms that help in correcting, analysing, and interpreting the resulting data. Additionally, we review some mathematical models that use single-cell and long-read sequencing data to study cell-fate determination and alternative splicing, respectively. Moreover, we highlight the emerging opportunities in modelling cell-fate determination that result from the combination of single-cell and long-read sequencing technologies.

Application of third-generation sequencing to herbal genomics

There is a long history of traditional medicine use. However, little genetic information is available for the plants used in traditional medicine, which limits the exploitation of these natural resources. Third-generation sequencing (TGS) techniques have made it possible to gather invaluable genetic information and develop herbal genomics. In this review, we introduce two main TGS techniques, PacBio SMRT technology and Oxford Nanopore technology, and compare the two techniques against Illumina, the predominant next-generation sequencing technique. In addition, we summarize the nuclear and organelle genome assemblies of commonly used medicinal plants, choose several examples from genomics, transcriptomics, and molecular identification studies to dissect the specific processes and summarize the advantages and disadvantages of the two TGS techniques when applied to medicinal organisms. Finally, we describe how we expect that TGS techniques will be widely utilized to assemble telomere-to-telomere (T2T) genomes and in epigenomics research involving medicinal plants.