Nanopore sequencing technology, bioinformatics and applications

A MinION-based Long-Read Sequencing Application With One-Step PCR for the Genetic Diagnosis of 21-Hydroxylase Deficiency

CONTEXT

Recently developed long-read sequencing (LRS) technology has been considered an option for CYP21A2 analysis. However, the clinical use of LRS for CYP21A2 analysis is limited.

OBJECTIVE

This study's objective is to develop an efficient and low-cost LRS system for CYP21A2 screening.

METHODS

A DNA fragment library was prepared in a single polymerase chain reaction (PCR) that covers the entire CYP21A2 gene and all known junctions caused by TNXB gene structural rearrangements, yielding a single 8-kb product of CYP21A2 or CYP21A1P/CYP21A2 chimera. After barcoding, the PCR products were sequenced on a MinION-based platform with Flongle Flow Cell R9.4.1 and R10.4.1.

RESULTS

The reference genotypes of 55 patients with 21-hydroxylase deficiency (21OHD) were established using the conventional method with multiplex ligation-dependent probe amplification (MLPA) and nested PCR. LRS using Flongle Flow Cell R9.4.1 yielded consistent results. Additionally, the recently updated LRS "duplex" analysis with Flongle flow cell R10.4.1 was tested to reveal an advantage of accurately sequencing a variant located on the homopolymer region. By introducing a barcode system, the cost was reduced to be comparable to that of conventional analysis. A novel single-nucleotide variation was discovered at the acceptor site of intron 7, c.940-1G > C. We also identified a subtype of the classical chimeric junction CH2, "CH2a," in the region from the latter part of intron 5 to exon 6.

CONCLUSION

We successfully established a novel low-cost and highly accurate LRS system for 21OHD genetic analysis. Our study provides insight into the feasibility of LRS for diagnosing 21OHD and other genetic diseases caused by structural rearrangements.

The high expression of TOP2A and MELK induces the occurrence of psoriasis

BACKGROUND

Psoriasis is a chronic inflammatory skin disease. However, the influence of the TOP2A and MELK genes on psoriasis remains unclear.

METHODS

Psoriasis datasets GSE166388 and GSE181318 were downloaded from the Gene Expression Omnibus (GEO) database generated from GPL570 and GPL22120. Differential gene expression (DEGs) was identified. Functional enrichment analysis, gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), and immune infiltration analysis were conducted. The protein-protein interaction (PPI) network was constructed and analyzed. Gene expression heat map was generated. The most relevant diseases associated with core genes were determined through comparison with the Comparative Toxicogenomics Database (CTD) website. TargetScan was used to select miRNAs regulating central DEGs.

RESULTS

A total of 773 DEGs were identified. According to Gene Ontology (GO) analysis, they were mainly enriched in mitochondrial gene expression, oxidative phosphorylation, mitochondrial envelope, mitochondria and ribosome. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that target cells were mainly enriched in metabolic pathways, proteasome, and oxidative phosphorylation. Seven core genes (TOP2A, NUF2, MELK, ASPM, DLGAP5, CCNA2, DEPDC1B) were obtained. The gene expression heatmap showed high expression of core genes (TOP2A, MELK) in psoriasis samples, while DEPDC1B, CCNA2, DLGAP5, NUF2, ASPM were lowly expressed in psoriasis samples. CTD analysis found that TOP2A and MELK were related to skin neoplasms, skin diseases, psoriasis, erythema, dermatitis, and infections.

CONCLUSION

TOP2A and MELK genes are highly expressed in psoriasis, and higher expression of TOP2A and MELK genes is associated with poorer prognosis.

Assessing the efficacy of target adaptive sampling long-read sequencing through hereditary cancer patient genomes

Innovations in sequencing technology have led to the discovery of novel mutations that cause inherited diseases. However, many patients with suspected genetic diseases remain undiagnosed. Long-read sequencing technologies are expected to significantly improve the diagnostic rate by overcoming the limitations of short-read sequencing. In addition, Oxford Nanopore Technologies (ONT) offers adaptive sampling and computationally driven target enrichment technology. This enables more affordable intensive analysis of target gene regions compared to standard non-selective long-read sequencing. In this study, we developed an efficient computational workflow for target adaptive sampling long-read sequencing (TAS-LRS) and evaluated it through application to 33 genomes collected from suspected hereditary cancer patients. Our workflow can identify single nucleotide variants with nearly the same accuracy as the short-read platform and elucidate complex forms of structural variations. We also newly identified several SINE-R/VNTR/Alu (SVA) elements affecting the APC gene in two patients with familial adenomatous polyposis, as well as their sites of origin. In addition, we demonstrated that off-target reads from adaptive sampling, which is typically discarded, can be effectively used to accurately genotype common single-nucleotide polymorphisms (SNPs) across the entire genome, enabling the calculation of a polygenic risk score. Furthermore, we identified allele-specific MLH1 promoter hypermethylation in a Lynch syndrome patient. In summary, our workflow with TAS-LRS can simultaneously capture monogenic risk variants including complex structural variations, polygenic background as well as epigenetic alterations, and will be an efficient platform for genetic disease research and diagnosis.

RUBICON: a framework for designing efficient deep learning-based genomic basecallers

Nanopore sequencing generates noisy electrical signals that need to be converted into a standard string of DNA nucleotide bases using a computational step called basecalling. The performance of basecalling has critical implications for all later steps in genome analysis. Therefore, there is a need to reduce the computation and memory cost of basecalling while maintaining accuracy. We present RUBICON, a framework to develop efficient hardware-optimized basecallers. We demonstrate the effectiveness of RUBICON by developing RUBICALL, the first hardware-optimized mixed-precision basecaller that performs efficient basecalling, outperforming the state-of-the-art basecallers. We believe RUBICON offers a promising path to develop future hardware-optimized basecallers.

DuBA.flow─A Low-Cost, Long-Read Amplicon Sequencing Workflow for the Validation of Synthetic DNA Constructs

Modern biological science, especially synthetic biology, relies heavily on the construction of DNA elements, often in the form of plasmids. Plasmids are used for a variety of applications, including the expression of proteins for subsequent purification, the expression of heterologous pathways for the production of valuable compounds, and the study of biological functions and mechanisms. For all applications, a critical step after the construction of a plasmid is its sequence validation. The traditional method for sequence determination is Sanger sequencing, which is limited to approximately 1000 bp per reaction. Here, we present a highly scalable in-house method for rapid validation of amplified DNA sequences using long-read Nanopore sequencing. We developed two-step amplicon and transposase strategies to provide maximum flexibility for dual barcode sequencing. We also provide an automated analysis pipeline to quickly and reliably analyze sequencing results and provide easy-to-interpret results for each sample. The user-friendly DuBA.flow start-to-finish pipeline is widely applicable. Furthermore, we show that construct validation using DuBA.flow can be performed by barcoded colony PCR amplicon sequencing, thus accelerating research.

Genomic characterization, in vitro, and preclinical evaluation of two microencapsulated lytic phages VB_ST_E15 and VB_ST_SPNIS2 against clinical multidrug-resistant Salmonella serovars

BACKGROUND

Salmonella infections continue to be one of the essential public health issues threatening millions of people. With the increasing occurrence of resistance against conventionally used antibiotics, the search for alternatives has become crucial. In this study, we aimed to isolate, characterize, and evaluate two lytic bacteriophages against clinically isolated multidrug-resistant (MDR) Salmonella serovars.

METHODS

Screening for the phage lytic activity was performed using a spot test. Characterization of the isolated phages was done by determining the host range, longevity test, and the effect of temperature, pH, organic solvents, and morphological characterization using a transmission electron microscope. Genomic analysis was performed using Oxford nanopore sequencing. The lytic activities of the free phage lysates and formulated phage as microencapsulated were evaluated both in vitro and in vivo.

RESULTS

Two phages (VB_ST_E15 and VB_ST_SPNIS2) were successfully isolated and showed lytic strong activities against MDR Salmonella (S.) Typhimurium ATCC 14,028, S. Paratyphi A, and S. Typhi. The two phages survived at the tested temperatures, maintained their infectivity for 90 days, and retained their activity until 60 °C with thermal inactivation at 65 °C. They were lytic at a pH range from 3 to 11 but lost their activities at extremely acidic or alkaline pH. The phages could withstand the organic solvents but were completely inactivated by 100% ethanol. Both phages were classified under the order Caudoviricetes, and Genus: Uetakevirus. Their genomic sequences were assembled, annotated, and submitted to the NCBI GenBank database (OR757455 and OR757456). The preclinical evaluation using the murine animal model revealed that the two-phage cocktail managed MDR Salmonella infection as evidenced by the reduction in the bacterial burden, increased animal weight, and histopathological examination.

CONCLUSION

The two encapsulated phage formulas could be considered promising candidates for the management of MDR Salmonella-associated infections and clinical analysis should be undertaken to evaluate their potential use in humans.

When Livestock Genomes Meet Third-Generation Sequencing Technology: From Opportunities to Applications

Third-generation sequencing technology has found widespread application in the genomic, transcriptomic, and epigenetic research of both human and livestock genetics. This technology offers significant advantages in the sequencing of complex genomic regions, the identification of intricate structural variations, and the production of high-quality genomes. Its attributes, including long sequencing reads, obviation of PCR amplification, and direct determination of DNA/RNA, contribute to its efficacy. This review presents a comprehensive overview of third-generation sequencing technologies, exemplified by single-molecule real-time sequencing (SMRT) and Oxford Nanopore Technology (ONT). Emphasizing the research advancements in livestock genomics, the review delves into genome assembly, structural variation detection, transcriptome sequencing, and epigenetic investigations enabled by third-generation sequencing. A comprehensive analysis is conducted on the application and potential challenges of third-generation sequencing technology for genome detection in livestock. Beyond providing valuable insights into genome structure analysis and the identification of rare genes in livestock, the review ventures into an exploration of the genetic mechanisms underpinning exemplary traits. This review not only contributes to our understanding of the genomic landscape in livestock but also provides fresh perspectives for the advancement of research in this domain.

Chemically Modified Platforms for Better RNA Therapeutics

RNA-based therapies have catalyzed a revolutionary transformation in the biomedical landscape, offering unprecedented potential in disease prevention and treatment. However, despite their remarkable achievements, these therapies encounter substantial challenges including low stability, susceptibility to degradation by nucleases, and a prominent negative charge, thereby hindering further development. Chemically modified platforms have emerged as a strategic innovation, focusing on precise alterations either on the RNA moieties or their associated delivery vectors. This comprehensive review delves into these platforms, underscoring their significance in augmenting the performance and translational prospects of RNA-based therapeutics. It encompasses an in-depth analysis of various chemically modified delivery platforms that have been instrumental in propelling RNA therapeutics toward clinical utility. Moreover, the review scrutinizes the rationale behind diverse chemical modification techniques aiming at optimizing the therapeutic efficacy of RNA molecules, thereby facilitating robust disease management. Recent empirical studies corroborating the efficacy enhancement of RNA therapeutics through chemical modifications are highlighted. Conclusively, we offer profound insights into the transformative impact of chemical modifications on RNA drugs and delineates prospective trajectories for their future development and clinical integration.

The Complete Mitochondrial Genome of Paeonia lactiflora Pall. (Saxifragales: Paeoniaceae): Evidence of Gene Transfer from Chloroplast to Mitochondrial Genome

Paeonia lactiflora (P. lactiflora), a perennial plant renowned for its medicinal roots, provides a unique case for studying the phylogenetic relationships of species based on organelle genomes, as well as the transference of DNA across organelle genomes. In order to investigate this matter, we sequenced and characterized the mitochondrial genome (mitogenome) of P. lactiflora. Similar to the chloroplast genome (cpgenome), the mitogenome of P. lactiflora extends across 181,688 base pairs (bp). Its unique quadripartite structure results from a pair of extensive inverted repeats, each measuring 25,680 bp in length. The annotated mitogenome includes 27 protein-coding genes, 37 tRNAs, 8 rRNAs, and two pseudogenes (rpl5, rpl16). Phylogenetic analysis was performed to identify phylogenetic trees consistent with Paeonia species phylogeny in the APG Ⅳ system. Moreover, a total of 12 MTPT events were identified and 32 RNA editing sites were detected during mitogenome analysis of P. lactiflora. Our research successfully compiled and annotated the mitogenome of P. lactiflora. The study provides valuable insights regarding the taxonomic classification and molecular evolution within the Paeoniaceae family.

Narrowing Signal Distribution by Adamantane Derivatization for Amino Acid Identification Using an α-Hemolysin Nanopore

The rapid progress in nanopore sensing has sparked interest in protein sequencing. Despite recent notable advancements in amino acid recognition using nanopores, chemical modifications usually employed in this process still need further refinements. One of the challenges is to enhance the chemical specificity to avoid downstream misidentification of amino acids. By employing adamantane to label proteinogenic amino acids, we developed an approach to fingerprint individual amino acids using the wild-type α-hemolysin nanopore. The unique structure of adamantane-labeled amino acids (ALAAs) improved the spatial resolution, resulting in distinctive current signals. Various nanopore parameters were explored using a machine-learning algorithm and achieved a validation accuracy of 81.3% for distinguishing nine selected amino acids. Our results not only advance the effort in single-molecule protein characterization using nanopores but also offer a potential platform for studying intrinsic and variant structures of individual molecules.

Precision Sequence-Defined Polymers: From Sequencing to Biological Functions

Precise sequence-defined polymers (SDPs) with uniform chain-to-chain structure including chain length, unit sequence, and end functionalities represent the pinnacle of sophistication in the realm of polymer science. For example, the absolute control over the unit sequence of SDPs allows for the bottom-up design of polymers with hierarchical microstructures and functions. Accompanied with the development of synthetic techniques towards precision SDPs, the decoding of SDP sequences and construction of advanced functions irreplaceable by other synthetic materials is of central importance. In this Minireview, we focus on recent advances in SDP sequencing techniques including tandem mass spectrometry (MS), chemically assisted primary MS, as well as other non-destructive sequencing methods such as nuclear magnetic resonance (NMR) spectroscopy, circular dichroism (CD), and nanopore sequencing. Additionally, we delve into the promising prospects of SDP functions in the area of cutting-edge biological research. Topics of exploration include gene delivery systems, the development of hybrid materials combining SDPs and nucleic acids, protein recognition and regulation, as well as the interplay between chirality and biological functions. A brief outlook towards the future directions of SDPs is also presented.

NanoCon: contrastive learning-based deep hybrid network for nanopore methylation detection

MOTIVATION

5-Methylcytosine (5mC), a fundamental element of DNA methylation in eukaryotes, plays a vital role in gene expression regulation, embryonic development, and other biological processes. Although several computational methods have been proposed for detecting the base modifications in DNA like 5mC sites from Nanopore sequencing data, they face challenges including sensitivity to noise, and ignoring the imbalanced distribution of methylation sites in real-world scenarios.

RESULTS

Here, we develop NanoCon, a deep hybrid network coupled with contrastive learning strategy to detect 5mC methylation sites from Nanopore reads. In particular, we adopted a contrastive learning module to alleviate the issues caused by imbalanced data distribution in nanopore sequencing, offering a more accurate and robust detection of 5mC sites. Evaluation results demonstrate that NanoCon outperforms existing methods, highlighting its potential as a valuable tool in genomic sequencing and methylation prediction. In addition, we also verified the effectiveness of our representation learning ability on two datasets by visualizing the dimension reduction of the features of methylation and nonmethylation sites from our NanoCon. Furthermore, cross-species and cross-5mC methylation motifs experiments indicated the robustness and the ability to perform transfer learning of our model. We hope this work can contribute to the community by providing a powerful and reliable solution for 5mC site detection in genomic studies.

AVAILABILITY AND IMPLEMENTATION

The project code is available at https://github.com/Challis-yin/NanoCon.

Next-generation forward genetic screens: uniting high-throughput perturbations with single-cell analysis

Programmable genome-engineering technologies, such as CRISPR (clustered regularly interspaced short palindromic repeats) nucleases and massively parallel CRISPR screens that capitalize on this programmability, have transformed biomedical science. These screens connect genes and noncoding genome elements to disease-relevant phenotypes, but until recently have been limited to individual phenotypes such as growth or fluorescent reporters of gene expression. By pairing massively parallel screens with high-dimensional profiling of single-cell types/states, we can now measure how individual genetic perturbations or combinations of perturbations impact the cellular transcriptome, proteome, and epigenome. We review technologies that pair CRISPR screens with single-cell multiomics and the unique opportunities afforded by extending pooled screens using deep multimodal phenotyping.

Exploring the transcriptional landscape of phage-host interactions using novel high-throughput approaches

In the last decade, powerful high-throughput sequencing approaches have emerged to analyse microbial transcriptomes at a global scale. However, to date, applications of these approaches to microbial viruses such as phages remain scarce. Tailoring these techniques to virus-infected bacteria promises to obtain a detailed picture of the underexplored RNA biology and molecular processes during infection. In addition, transcriptome study of stress and perturbations induced by phages in their infected bacterial hosts is likely to reveal new fundamental mechanisms of bacterial metabolism and gene regulation. Here, we provide references and blueprints to implement emerging transcriptomic approaches towards addressing transcriptome architecture, RNA-RNA and RNA-protein interactions, RNA modifications, structures and heterogeneity of transcription profiles in infected cells that will provide guides for future directions in phage-centric therapeutic applications and microbial synthetic biology.

Advances in next-generation sequencing and emerging technologies for hematologic malignancies

Innovations in molecular diagnostics have often evolved through the study of hematologic malignancies. Examples include the pioneering characterization of the Philadelphia chromosome by cytogenetics in the 1970s, the implementation of polymerase chain reaction for high-sensitivity detection and monitoring of mutations and, most recently, targeted next- generation sequencing to drive the prognostic and therapeutic assessment of leukemia. Hematologists and hematopath- ologists have continued to advance in the past decade with new innovations improving the type, amount, and quality of data generated for each molecule of nucleic acid. In this review article, we touch on these new developments and discuss their implications for diagnostics in hematopoietic malignancies. We review advances in sequencing platforms and library preparation chemistry that can lead to faster turnaround times, novel sequencing techniques, the development of mobile laboratories with implications for worldwide benefits, the current status of sample types, improvements to quality and reference materials, bioinformatic pipelines, and the integration of machine learning and artificial intelligence into mol- ecular diagnostic tools for hematologic malignancies.

Highly efficient clustering of long-read transcriptomic data with GeLuster

MOTIVATION

The advancement of long-read RNA sequencing technologies leads to a bright future for transcriptome analysis, in which clustering long reads according to their gene family of origin is of great importance. However, existing de novo clustering algorithms require plenty of computing resources.

RESULTS

We developed a new algorithm GeLuster for clustering long RNA-seq reads. Based on our tests on one simulated dataset and nine real datasets, GeLuster exhibited superior performance. On the tested Nanopore datasets it ran 2.9-17.5 times as fast as the second-fastest method with less than one-seventh of memory consumption, while achieving higher clustering accuracy. And on the PacBio data, GeLuster also had a similar performance. It sets the stage for large-scale transcriptome study in future.

AVAILABILITY AND IMPLEMENTATION

GeLuster is freely available at https://github.com/yutingsdu/GeLuster.

Data Storage Using DNA

The exponential growth of global data has outpaced the storage capacities of current technologies, necessitating innovative storage strategies. DNA, as a natural medium for preserving genetic information, has emerged as a highly promising candidate for next-generation storage medium. Storing data in DNA offers several advantages, including ultrahigh physical density and exceptional durability. Facilitated by significant advancements in various technologies, such as DNA synthesis, DNA sequencing, and DNA nanotechnology, remarkable progress has been made in the field of DNA data storage over the past decade. However, several challenges still need to be addressed to realize practical applications of DNA data storage. In this review, the processes and strategies of in vitro DNA data storage are first introduced, highlighting recent advancements. Next, a brief overview of in vivo DNA data storage is provided, with a focus on the various writing strategies developed to date. At last, the challenges encountered in each step of DNA data storage are summarized and promising techniques are discussed that hold great promise in overcoming these obstacles.

Metabarcoding using nanopore long-read sequencing for the unbiased characterization of apicomplexan haemoparasites

Apicomplexan haemoparasites generate significant morbidity and mortality in humans and other animals, particularly in many low-to-middle income countries. Malaria caused by Plasmodium remains responsible for some of the highest numbers of annual deaths of any human pathogen, whilst piroplasmids, such as Babesia and Theileria can have immense negative economic effects through livestock loss. Diagnosing haemoparasites via traditional methods like microscopy is challenging due to low-level and transient parasitaemia. PCR-based diagnostics overcome these limitations by being both highly sensitive and specific, but they may be unable to accurately detect coinfections or identify novel species. In contrast, next-generation sequencing (NGS)-based methods can characterize all pathogens from a group of interest concurrently, although, the short-read platforms previously used have been limited in the taxonomic resolution achievable. Here, we used Oxford Nanopore Technologies' (ONT) long-read MinION™ sequencer to conduct apicomplexan haemoparasite metabarcoding via sequencing the near full-length 18S ribosomal RNA gene, demonstrating its ability to detect Babesia, Hepatozoon, Neospora, Plasmodium, Theileria and Toxoplasma species. This method was tested on blood-extracted DNA from 100 dogs and the results benchmarked against qPCR and Illumina-based metabarcoding. For two common haemoparasites, nanopore sequencing performed as well as qPCR (kappa agreement statistics > 0.98), whilst also detecting one pathogen, Hepatozoon felis, missed by the other techniques. The long-reads obtained by nanopore sequencing provide an improved species-level taxonomic resolution whilst the method's broad applicability mean it can be used to explore apicomplexan communities from diverse mammalian hosts, on a portable sequencer that easily permits adaptation to field use.

The long and short of it: benchmarking viromics using Illumina, Nanopore and PacBio sequencing technologies

Viral metagenomics has fuelled a rapid change in our understanding of global viral diversity and ecology. Long-read sequencing and hybrid assembly approaches that combine long- and short-read technologies are now being widely implemented in bacterial genomics and metagenomics. However, the use of long-read sequencing to investigate viral communities is still in its infancy. While Nanopore and PacBio technologies have been applied to viral metagenomics, it is not known to what extent different technologies will impact the reconstruction of the viral community. Thus, we constructed a mock bacteriophage community of previously sequenced phage genomes and sequenced them using Illumina, Nanopore and PacBio sequencing technologies and tested a number of different assembly approaches. When using a single sequencing technology, Illumina assemblies were the best at recovering phage genomes. Nanopore- and PacBio-only assemblies performed poorly in comparison to Illumina in both genome recovery and error rates, which both varied with the assembler used. The best Nanopore assembly had errors that manifested as SNPs and INDELs at frequencies 41 and 157 % higher than found in Illumina only assemblies, respectively. While the best PacBio assemblies had SNPs at frequencies 12 and 78 % higher than found in Illumina-only assemblies, respectively. Despite high-read coverage, long-read-only assemblies recovered a maximum of one complete genome from any assembly, unless reads were down-sampled prior to assembly. Overall the best approach was assembly by a combination of Illumina and Nanopore reads, which reduced error rates to levels comparable with short-read-only assemblies. When using a single technology, Illumina only was the best approach. The differences in genome recovery and error rates between technology and assembler had downstream impacts on gene prediction, viral prediction, and subsequent estimates of diversity within a sample. These findings will provide a starting point for others in the choice of reads and assembly algorithms for the analysis of viromes.

Implementation of full-length 16S nanopore sequencing for bacterial identification in a clinical diagnostic setting

This study describes the implementation of 16S nanopore sequencing in a diagnostic lab for pathogen identification without prior enrichment. First, the universality of the test and taxonomic resolution was evaluated for 78 clinically relevant bacteria (69 known and 9 unknown bacterial cultures). Next, the diagnostic value of the test was evaluated based on clinical samples. It was shown that 16S sequencing can be used both for identification of unknown cultures and to find bacteria directly in the clinical sample without cultivation. All culture-positive samples (n=11) tested positive with 16S sequencing directly performed on the sample, but bacteria were found as well in 15/30 culture-negative samples. Pathogenic bacteria were found in a background of commensal flora, and even complex polymicrobial infections could be unraveled. This study demonstrates the feasibility of implementing 16S nanopore sequencing in a clinical diagnostic setting and demonstrates its value for the diagnosis of culture-negative and polymicrobial infections.

DNA data storage in electrospun and melt-electrowritten composite nucleic acid-polymer fibers

Incorporating biomolecules as integral parts of computational systems represents a frontier challenge in bio- and nanotechnology. Using DNA to store digital data is an attractive alternative to conventional information technologies due to its high information density and long lifetime. However, developing an adequate DNA storage medium remains a significant challenge in permitting the safe archiving and retrieval of oligonucleotides. This work introduces composite nucleic acid-polymer fibers as matrix materials for digital information-bearing oligonucleotides. We devised a complete workflow for the stable storage of DNA in PEO, PVA, and PCL fibers by employing electrohydrodynamic processes to produce electrospun nanofibers with embedded oligonucleotides. The on-demand retrieval of messages is afforded by non-hazardous chemical treatment and subsequent PCR amplification and DNA sequencing. Finally, we develop a platform for melt-electrowriting of polymer-DNA composites to produce microfiber meshes of programmable patterns and geometries.

Long-Read Sequencing and De Novo Genome Assembly Pipeline of Two Plasmodium falciparum Clones (Pf3D7, PfW2) Using Only the PromethION Sequencer from Oxford Nanopore Technologies without Whole-Genome Amplification

Antimalarial drug resistance has become a real public health problem despite WHO measures. New sequencing technologies make it possible to investigate genomic variations associated with resistant phenotypes at the genome-wide scale. Based on the use of hemisynthetic nanopores, the PromethION technology from Oxford Nanopore Technologies can produce long-read sequences, in contrast to previous short-read technologies used as the gold standard to sequence Plasmodium. Two clones of P. falciparum (Pf3D7 and PfW2) were sequenced in long-read using the PromethION sequencer from Oxford Nanopore Technologies without genomic amplification. This made it possible to create a processing analysis pipeline for human Plasmodium with ONT Fastq only. De novo assembly revealed N50 lengths of 18,488 kb and 17,502 kb for the Pf3D7 and PfW2, respectively. The genome size was estimated at 23,235,407 base pairs for the Pf3D7 clone and 21,712,038 base pairs for the PfW2 clone. The average genome coverage depth was estimated at 787X and 653X for the Pf3D7 and PfW2 clones, respectively. This study proposes an assembly processing pipeline for the human Plasmodium genome using software adapted to large ONT data and the high AT percentage of Plasmodium. This search provides all the parameters which were optimized for use with the software selected in the pipeline.

Full-length transcriptome reveals the pivotal role of ABA and ethylene in the cold stress response of Tetrastigma hemsleyanum

Tetrastigma hemsleyanum is a valuable herb widely used in Chinese traditional and modern medicine. Winter cold severely limits the artificial cultivation of this plant, but the physiological and molecular mechanisms upon exposure to cold stress in T. hemsleyanum are unclear. T. hemsleyanum plants with different geographical origins exhibit large differences in response to cold stress. In this research study, using T. hemsleyanum ecotypes that exhibit frost tolerance (FR) and frost sensitivity (FS), we analyzed the response of cottage seedlings to a simulated frost treatment; plant hormones were induced with both short (2 h) and long (9 h) frost treatments, which were used to construct the full-length transcriptome and obtained 76,750 transcripts with all transcripts mapped to 28,805 genes, and 27,215 genes, respectively, annotated to databases. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed enrichment in plant hormone signaling pathways. Further analysis shows that differently expressed genes (DEGs) concentrated on calcium signaling, ABA biosynthesis and signal transduction, and ethylene in response to cold stress. We also found that endogenous ABA and ethylene content were increased after cold treatment, and exogenous ABA and ethylene significantly improved cold tolerance in both ecotypes. Our results elucidated the pivotal role of ABA and ethylene in response to cold stress in T. hemsleyanum and identified key genes.

Nanopore sequencing of infectious fluid is a promising supplement for gold-standard culture in real-world clinical scenario

Introduction

Infectious diseases are major causes of morbidity and mortality worldwide, necessitating the rapid identification and accurate diagnosis of pathogens. While unbiased metagenomic next-generation sequencing (mNGS) has been extensively utilized in clinical pathogen identification and scientific microbiome detection, there is limited research about the application of nanopore platform-based mNGS in the diagnostic performance of various infectious fluid samples.

Methods

In this study, we collected 297 suspected infectious fluids from 10 clinical centers and detected them with conventional microbiology culture and nanopore platform-based mNGS. The objective was to assess detective and diagnostic performance of nanopore-sequencing technology (NST) in real-world scenarios.

Results

Combined with gold-standard culture and clinical adjudication, nanopore sequencing demonstrated nearly 100% positive predictive agreements in microbial-colonized sites, such as the respiratory and urinary tracts. For samples collected from initially sterile body sites, the detected microorganisms were highly suspected pathogens, and the negative predictive agreements were relatively higher than those in the microbial-colonized sites, particularly with 100% in abscess and 95.7% in cerebrospinal fluid. Furthermore, consistent performance was also observed in the identification of antimicrobial resistance genes and drug susceptibility testing of pathogenic strains of Escherichia coli, Staphylococcus aureus, and Acinetobacter baumannii.

Discussion

Rapid NST is a promising clinical tool to supplement gold-standard culture, and it has the potential improve patient prognosis and facilitate clinical treatment of infectious diseases.

Single-Crystal Silicon Nanotubes, Hollow Nanocones, and Branched Nanotube Networks

We report a general approach for the synthesis of single-crystal silicon nanotubes, involving epitaxial deposition of silicon shells on germanium nanowire templates followed by removal of the germanium template by selective wet etching. By exploiting advances in the synthesis of germanium nanowires, we were able to rationally tune the nanotube internal diameters (5-80 nm), wall thicknesses (3-12 nm), and taper angles (0-9°) and additionally demonstrated branched silicon nanotube networks. Field effect transistors fabricated from p-type nanotubes exhibited a strong gate effect, and fluid transport experiments demonstrated that small molecules could be electrophoretically driven through the nanotubes. These results demonstrate the suitability of silicon nanotubes for the design of nanoelectrofluidic devices.

Application of next-generation sequencing to identify different pathogens

Early and precise detection and identification of various pathogens are essential for epidemiological monitoring, disease management, and reducing the prevalence of clinical infectious diseases. Traditional pathogen detection techniques, which include mass spectrometry, biochemical tests, molecular testing, and culture-based methods, are limited in application and are time-consuming. Next generation sequencing (NGS) has emerged as an essential technology for identifying pathogens. NGS is a cutting-edge sequencing method with high throughput that can create massive volumes of sequences with a broad application prospects in the field of pathogen identification and diagnosis. In this review, we introduce NGS technology in detail, summarizes the application of NGS in that identification of different pathogens, including bacteria, fungi, and viruses, and analyze the challenges and outlook for using NGS to identify clinical pathogens. Thus, this work provides a theoretical basis for NGS studies and provides evidence to support the application of NGS in distinguishing various clinical pathogens.

Unraveling metagenomics through long-read sequencing: a comprehensive review

The study of microbial communities has undergone significant advancements, starting from the initial use of 16S rRNA sequencing to the adoption of shotgun metagenomics. However, a new era has emerged with the advent of long-read sequencing (LRS), which offers substantial improvements over its predecessor, short-read sequencing (SRS). LRS produces reads that are several kilobases long, enabling researchers to obtain more complete and contiguous genomic information, characterize structural variations, and study epigenetic modifications. The current leaders in LRS technologies are Pacific Biotechnologies (PacBio) and Oxford Nanopore Technologies (ONT), each offering a distinct set of advantages. This review covers the workflow of long-read metagenomics sequencing, including sample preparation (sample collection, sample extraction, and library preparation), sequencing, processing (quality control, assembly, and binning), and analysis (taxonomic annotation and functional annotation). Each section provides a concise outline of the key concept of the methodology, presenting the original concept as well as how it is challenged or modified in the context of LRS. Additionally, the section introduces a range of tools that are compatible with LRS and can be utilized to execute the LRS process. This review aims to present the workflow of metagenomics, highlight the transformative impact of LRS, and provide researchers with a selection of tools suitable for this task.

Il1r2 and Tnfrsf12a in transcranial magnetic stimulation effect of ischemic stroke via bioinformatics analysis

Ischemic stroke refers to ischemic necrosis or softening of localized brain tissue. Transcranial magnetic stimulation (TMS) is a painless, noninvasive and green treatment method, which acts on the central nervous system through a pulsed magnetic field to assist in the treatment of central nervous system injury diseases. However, the role of Il1r2 and Tnfrsf12a in this is unknown. The ischemic stroke datasets GSE81302 and TMS datasets GSE230148 were downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened and weighted gene co-expression network analysis (WGCNA) was performed. The construction and analysis of protein-protein interaction (PPI) network and functional enrichment analysis were performed. Draw heat map gene expression. Through the Comparative Toxicogenomics Database (CTD) to find the most relevant and core gene diseases. TargetScan was used to screen miRNAs regulating DEGs. A total of 39 DEGs were identified. According to gene ontology (GO) analysis results, in biological process (BP) analysis, they were mainly enriched in the positive regulation of apoptosis process, inflammatory response, positive regulation of p38MAPK cascade, and regulation of cell cycle. In cellular component (CC) analysis, they were mainly enriched in the cell surface, cytoplasm, and extracellular space. In Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, they were mainly enriched in nf-κB signaling pathway, fluid shear stress and atherosclerosis, P53 signaling pathway, TNF signaling pathway, and apoptosis. Among the enrichment items of metascape, negative regulation of T cell activation, hematopoietic cell lineage, positive regulation of apoptotic process, fluid shear stress and atherosclerosis were observed in GO enrichment items. Five core genes (Socs3, Irf1, Il1r2, Ccr1, and Tnfrsf12a) were obtained, which were highly expressed in ischemic stroke samples. Il1r2 and Tnfrsf12a were lowly expressed in TMS samples. CTD analysis found that the core gene (Socs3, Irf1 and Il1r2, Ccr1, Tnfrsf12a) and ischemic stroke, atherosclerosis, hypertension, hyperlipidemia, thrombosis, stroke, myocardial ischemia, myocardial infarction, and inflammation. Il1r2 and Tnfrsf12a are highly expressed in ischemic stroke, but lowly expressed in TMS samples.

Machine learning identifies SLC6A14 as a novel biomarker promoting the proliferation and metastasis of pancreatic cancer via Wnt/β-catenin signaling

Pancreatic cancer (PC) has the poorest prognosis compared to other common cancers because of its aggressive nature, late detection, and resistance to systemic treatment. In this study, we aimed to identify novel biomarkers for PC patients and further explored their function in PC progression. We analyzed GSE62452 and GSE28735 datasets, identifying 35 differentially expressed genes (DEGs) between PC specimens and non-tumors. Based on 35 DEGs, we performed machine learning and identified eight diagnostic genes involved in PC progression. Then, we further screened three critical genes (CTSE, LAMC2 and SLC6A14) using three GEO datasets. A new diagnostic model was developed based on them and showed a strong predictive ability in screen PC specimens from non-tumor specimens in GEO, TCGA datasets and our cohorts. Then, clinical assays based on TCGA datasets indicated that the expression of LAMC2 and SLC6A14 was associated with advanced clinical stage and poor prognosis. The expressions of LAMC2 and SLC6A14, as well as the abundances of a variety of immune cells, exhibited a significant positive association with one another. Functionally, we confirmed that SLC6A14 was highly expressed in PC and its knockdown suppressed the proliferation, migration, invasion and EMT signal via regulating Wnt/β-catenin signaling pathway. Overall, our findings developed a novel diagnostic model for PC patients. SLC6A14 may promote PC progression via modulating Wnt/β-catenin signaling. This work offered a novel and encouraging new perspective that holds potential for further illuminating the clinicopathological relevance of PC as well as its molecular etiology.

Three Rounds of Read Correction Significantly Improve Eukaryotic Protein Detection in ONT Reads

BACKGROUND

Eukaryotes' whole-genome sequencing is crucial for species identification, gene detection, and protein annotation. Oxford Nanopore Technology (ONT) is an affordable and rapid platform for sequencing eukaryotes; however, the relatively higher error rates require computational and bioinformatic efforts to produce more accurate genome assemblies. Here, we evaluated the effect of read correction tools on eukaryote genome completeness, gene detection and protein annotation.

METHODS

Reads generated by ONT of four eukaryotes, C. albicans, C. gattii, S. cerevisiae, and P. falciparum, were assembled using minimap2 and underwent three rounds of read correction using flye, medaka and racon. The generates consensus FASTA files were compared for total length (bp), genome completeness, gene detection, and protein-annotation by QUAST, BUSCO, BRAKER1 and InterProScan, respectively.

RESULTS

Genome completeness was dependent on the assembly method rather than on the read correction tool; however, medaka performed better than flye and racon. Racon significantly performed better than flye and medaka in gene detection, while both racon and medaka significantly performed better than flye in protein-annotation.

CONCLUSION

We show that three rounds of read correction significantly affect gene detection and protein annotation, which are dependent on assembly quality in preference to assembly completeness.

Selective Sensing of DNA Nucleobases with Angular Discrimination

The fast and precise selective sensing of DNA nucleobases is a long-pursued method that can lead to huge advances in the field of genomics and have an impact on aspects such as the prevention of diseases, health enhancement, and, in general, all types of medical treatments. We present here a new type of nanoscale sensor based on carbon nanotubes with a specific geometry that can discriminate the type of nucleobase and also its angle of orientation. The proper differentiation of nucleobases is essential to clearly sequence DNA chains, while angular discrimination is key to improving the sensing selectivity. We perform first-principle and quantum transport simulations to calculate the transmission, conductance, and current of the nanotube-based nanoscale sensor in the presence of the four nucleotides (A, C, G, and T), each of them rotated 0, 90, 180, or 270°. Our results show that this system is able to effectively discriminate between the four nucleotides and their angle of orientation. We explain these findings in terms of the interaction between the phosphate group of the nucleotide and the nanotube wall. The phosphate specifically distorts the electronic structure of the nanotube depending on the distance and the orientation and leads to nontrivial changes in the transmission. This work provides a method for finer and more precise sequential DNA chains.

Development and validation of a long-read metabarcoding platform for the detection of filarial worm pathogens of animals and humans

BACKGROUND

Filarial worms are important vector-borne pathogens of a large range of animal hosts, including humans, and are responsible for numerous debilitating neglected tropical diseases such as, lymphatic filariasis caused by Wuchereria bancrofti and Brugia spp., as well as loiasis caused by Loa loa. Moreover, some emerging or difficult-to-eliminate filarioid pathogens are zoonotic using animals like canines as reservoir hosts, for example Dirofilaria sp. 'hongkongensis'. Diagnosis of filariasis through commonly available methods, like microscopy, can be challenging as microfilaremia may wane below the limit of detection. In contrast, conventional PCR methods are more sensitive and specific but may show limited ability to detect coinfections as well as emerging and/or novel pathogens. Use of deep-sequencing technologies obviate these challenges, providing sensitive detection of entire parasite communities, whilst also being better suited for the characterisation of rare or novel pathogens. Therefore, we developed a novel long-read metabarcoding assay for deep-sequencing the filarial nematode cytochrome c oxidase subunit I gene on Oxford Nanopore Technologies' (ONT) MinION™ sequencer. We assessed the overall performance of our assay using kappa statistics to compare it to commonly used diagnostic methods for filarial worm detection, such as conventional PCR (cPCR) with Sanger sequencing and the microscopy-based modified Knott's test (MKT).

RESULTS

We confirmed our metabarcoding assay can characterise filarial parasites from a diverse range of genera, including, Breinlia, Brugia, Cercopithifilaria, Dipetalonema, Dirofilaria, Onchocerca, Setaria, Stephanofilaria and Wuchereria. We demonstrated proof-of-concept for this assay by using blood samples from Sri Lankan dogs, whereby we identified infections with the filarioids Acanthocheilonema reconditum, Brugia sp. Sri Lanka genotype and zoonotic Dirofilaria sp. 'hongkongensis'. When compared to traditionally used diagnostics, such as the MKT and cPCR with Sanger sequencing, we identified an additional filarioid species and over 15% more mono- and coinfections.

CONCLUSIONS

Our developed metabarcoding assay may show broad applicability for the metabarcoding and diagnosis of the full spectrum of filarioids from a wide range of animal hosts, including mammals and vectors, whilst the utilisation of ONT' small and portable MinION™ means that such methods could be deployed for field use.

Resolving Genotype-Phenotype Discrepancies of the Kidd Blood Group System Using Long-Read Nanopore Sequencing

Due to substantial improvements in read accuracy, third-generation long-read sequencing holds great potential in blood group diagnostics, particularly in cases where traditional genotyping or sequencing techniques, primarily targeting exons, fail to explain serological phenotypes. In this study, we employed Oxford Nanopore sequencing to resolve all genotype-phenotype discrepancies in the Kidd blood group system (JK, encoded by SLC14A1) observed over seven years of routine high-throughput donor genotyping using a mass spectrometry-based platform at the Blood Transfusion Service, Zurich. Discrepant results from standard serological typing and donor genotyping were confirmed using commercial PCR-SSP kits. To resolve discrepancies, we amplified the entire coding region of SLC14A1 (~24 kb, exons 3 to 10) in two overlapping long-range PCRs in all samples. Amplicons were barcoded and sequenced on a MinION flow cell. Sanger sequencing and bridge-PCRs were used to confirm findings. Among 11,972 donors with both serological and genotype data available for the Kidd system, we identified 10 cases with unexplained conflicting results. Five were linked to known weak and null alleles caused by variants not included in the routine donor genotyping. In two cases, we identified novel null alleles on the JK*01 (Gly40Asp; c.119G>A) and JK*02 (Gly242Glu; c.725G>A) haplotypes, respectively. Remarkably, the remaining three cases were associated with a yet unknown deletion of ~5 kb spanning exons 9-10 of the JK*01 allele, which other molecular methods had failed to detect. Overall, nanopore sequencing demonstrated reliable and accurate performance for detecting both single-nucleotide and structural variants. It possesses the potential to become a robust tool in the molecular diagnostic portfolio, particularly for addressing challenging structural variants such as hybrid genes, deletions and duplications.

The Evolution, Assembly, and Dynamics of Marine Holobionts

The holobiont concept (i.e., multiple living beings in close symbiosis with one another and functioning as a unit) is revolutionizing our understanding of biology, especially in marine systems. The earliest marine holobiont was likely a syntrophic partnership of at least two prokaryotic members. Since then, symbiosis has enabled marine organisms to conquer all ocean habitats through the formation of holobionts with a wide spectrum of complexities. However, most scientific inquiries have focused on isolated organisms and their adaptations to specific environments. In this review, we attempt to illustrate why a holobiont perspective-specifically, the study of how numerous organisms form a discrete ecological unit through symbiosis-will be a more impactful strategy to advance our understanding of the ecology and evolution of marine life. We argue that this approach is instrumental in addressing the threats to marine biodiversity posed by the current global environmental crisis.

Selective whole-genome sequencing of Plasmodium parasites directly from blood samples by nanopore adaptive sampling

IMPORTANCE

Malaria is caused by parasites of the genus Plasmodium, and reached a global disease burden of 247 million cases in 2021. To study drug resistance mutations and parasite population dynamics, whole-genome sequencing of patient blood samples is commonly performed. However, the predominance of human DNA in these samples imposes the need for time-consuming laboratory procedures to enrich Plasmodium DNA. We used the Oxford Nanopore Technologies' adaptive sampling feature to circumvent this problem and enrich Plasmodium reads directly during the sequencing run. We demonstrate that adaptive nanopore sequencing efficiently enriches Plasmodium reads, which simplifies and shortens the timeline from blood collection to parasite sequencing. In addition, we show that the obtained data can be used for monitoring genetic markers, or to generate nearly complete genomes. Finally, owing to its inherent mobility, this technology can be easily applied on-site in endemic areas where patients would benefit the most from genomic surveillance.

Comparative Analysis of Multiple Consensus Genomes of the Same Strain of Marek's Disease Virus Reveals Intrastrain Variation

Current strategies to understand the molecular basis of Marek's disease virus (MDV) virulence primarily consist of cataloguing divergent nucleotides between strains with different phenotypes. However, each MDV strain is typically represented by a single consensus genome despite the confirmed existence of mixed viral populations. To assess the reliability of single-consensus interstrain genomic comparisons, we obtained two additional consensus genomes of vaccine strain CVI988 (Rispens) and two additional consensus genomes of the very virulent strain Md5 by sequencing viral stocks and cultured field isolates. In conjunction with the published genomes of CVI988 and Md5, this allowed us to perform 3-way comparisons between consensus genomes of the same strain. We found that consensus genomes of CVI988 can vary in as many as 236 positions involving 13 open reading frames (ORFs). In contrast, we found that Md5 genomes varied only in 11 positions involving a single ORF. Phylogenomic analyses showed all three Md5 consensus genomes clustered closely together, while also showing that CVI988 GenBank.BAC diverged from CVI988 Pirbright.lab and CVI988 USDA.PA.field . Comparison of CVI988 consensus genomes revealed 19 SNPs in the unique regions of CVI988 GenBank.BAC that were not present in either CVI988 Pirbright.lab or CVI988 USDA.PA.field . Finally, we evaluated the genomic heterogeneity of CVI988 and Md5 populations by identifying positions with >2% read support for alternative alleles in two ultra-deeply sequenced samples. We were able to confirm that both populations of CVI988 and Md5 were mixed, exhibiting a total of 29 and 27 high-confidence minor variant positions, respectively. We did not find any evidence of minor variants in the positions corresponding to the 19 SNPs in the unique regions of CVI988 GenBank.BAC . Taken together, our findings confirm that consensus genomes of the same strain of MDV can vary and suggest that multiple consensus genomes per strain are needed in order to maximize the accuracy of interstrain genomic comparisons.

NASCarD (Nanopore Adaptive Sampling with Carrier DNA): A Rapid, PCR-Free Method for SARS-CoV-2 Whole-Genome Sequencing in Clinical Samples

Whole-genome sequencing (WGS) represents the main technology for SARS-CoV-2 lineage characterization in diagnostic laboratories worldwide. The rapid, near-full-length sequencing of the viral genome is commonly enabled by high-throughput sequencing of PCR amplicons derived from cDNA molecules. Here, we present a new approach called NASCarD (Nanopore Adaptive Sampling with Carrier DNA), which allows a low amount of nucleic acids to be sequenced while selectively enriching for sequences of interest, hence limiting the production of non-target sequences. Using COVID-19 positive samples available during the omicron wave, we demonstrate how the method may lead to >99% genome completeness of the SARS-CoV-2 genome sequences within 7 h of sequencing at a competitive cost. The new approach may have applications beyond SARS-CoV-2 sequencing for other DNA or RNA pathogens in clinical samples.

Long amplicon nanopore sequencing of Botrytis cinerea and other fungal species present in infected grapevine leaf samples

Botrytis cinerea is a well-known plant pathogen responsible for grey mould disease infecting more than 500 plant species. It is listed as the second most important plant pathogen scientifically and economically. Its impact is particularly severe in grapes since it affects both the yield of grape berries and the quality of wines. While various methods for detecting B. cinerea have been investigated, the application of Oxford Nanopore Technology (ONT) for complete ribosomal operon sequencing, which has proven effective in human and animal fungal research and diagnostics, has not yet been explored in grapevine (Vitis vinifera) disease research. In this study, we sequenced complete ribosomal operons (∼5.5 kb amplicons), which encompass the 18S, ITS1, 5.8S, ITS2, and 28S regions, from both pure cultures of B. cinerea and infected grapevine leaf samples. Minimap2, a sequence alignment tool integrated into the EPI2ME software, served as a taxonomy classifier, utilizing the custom reference database FRODO. The results demonstrate that B. cinerea was detectable when this pathogen was not the dominant fungal species in leaf samples. Additionally, the method facilitates host DNA-free sequencing and might have a good potential to distinguish other pathogenic and non-pathogenic fungal species hosted within grapevine's infected leaves, such as Alternaria alternata, Saccharomyces cerevisiae, Saccharomyces boulardii, Mucor racemosus, and Ascochyta rabie. The sequences were uploaded to the NCBI database. Long amplicon sequencing method has the capacity to be broadened to other susceptible crops and pathogens, as a valuable tool for early grey rot detection and mycobiome research. Future large-scale studies are needed to overcome challenges, such as comprehensive reference databases for complete fungal ribosomal operons for grape mycobiome studies.

Integrative genotyping of cancer and immune phenotypes by long-read sequencing

Single-cell transcriptomics has become the definitive method for classifying cell types and states, and can be augmented with genotype information to improve cell lineage identification. Due to constraints of short-read sequencing, current methods to detect natural genetic barcodes often require cumbersome primer panels and early commitment to targets. Here we devise a flexible long-read sequencing workflow and analysis pipeline, termed nanoranger, that starts from intermediate single-cell cDNA libraries to detect cell lineage-defining features, including single-nucleotide variants, fusion genes, isoforms, sequences of chimeric antigen and TCRs. Through systematic analysis of these classes of natural 'barcodes', we define the optimal targets for nanoranger, namely those loci close to the 5' end of highly expressed genes with transcript lengths shorter than 4 kB. As proof-of-concept, we apply nanoranger to longitudinal tracking of subclones of acute myeloid leukemia (AML) and describe the heterogeneous isoform landscape of thousands of marrow-infiltrating immune cells. We propose that enhanced cellular genotyping using nanoranger can improve the tracking of single-cell tumor and immune cell co-evolution.

Streamlining remote nanopore data access with slow5curl

BACKGROUND

As adoption of nanopore sequencing technology continues to advance, the need to maintain large volumes of raw current signal data for reanalysis with updated algorithms is a growing challenge. Here we introduce slow5curl, a software package designed to streamline nanopore data sharing, accessibility, and reanalysis.

RESULTS

Slow5curl allows a user to fetch a specified read or group of reads from a raw nanopore dataset stored on a remote server, such as a public data repository, without downloading the entire file. Slow5curl uses an index to quickly fetch specific reads from a large dataset in SLOW5/BLOW5 format and highly parallelized data access requests to maximize download speeds. Using all public nanopore data from the Human Pangenome Reference Consortium (>22 TB), we demonstrate how slow5curl can be used to quickly fetch and reanalyze raw signal reads corresponding to a set of target genes from each individual in large cohort dataset (n = 91), minimizing the time, egress costs, and local storage requirements for their reanalysis.

CONCLUSIONS

We provide slow5curl as a free, open-source package that will reduce frictions in data sharing for the nanopore community: https://github.com/BonsonW/slow5curl.

A review of innovative electrochemical strategies for bioactive molecule detection and cell imaging: Current advances and challenges

Cellular heterogeneity poses a major challenge for tumor theranostics, requiring high-resolution intercellular bioanalysis strategies. Over the past decades, the advantages of electrochemical analysis, such as high sensitivity, good spatio-temporal resolution, and ease of use, have made it the preferred method to uncover cellular differences. To inspire more creative research, herein, we highlight seminal works in electrochemical techniques for biomolecule analysis and bioimaging. Specifically, micro/nano-electrode-based electrochemical techniques enable real-time quantitative analysis of electroactive substances relevant to life processes in the micro-nanostructure of cells and tissues. Nanopore-based technique plays a vital role in biosensing by utilizing nanoscale pores to achieve high-precision detection and analysis of biomolecules with exceptional sensitivity and single-molecule resolution. Electrochemiluminescence (ECL) technology is utilized for real-time monitoring of the behavior and features of individual cancer cells, enabling observation of their dynamic processes due to its capability of providing high-resolution and highly sensitive bioimaging of cells. Particularly, scanning electrochemical microscopy (SECM) and scanning ion conductance microscopy (SICM) which are widely used in real-time observation of cell surface biological processes and three-dimensional imaging of micro-nano structures, such as metabolic activity, ion channel activity, and cell morphology are introduced in this review. Furthermore, the expansion of the scope of cellular electrochemistry research by innovative functionalized electrodes and electrochemical imaging models and strategies to address future challenges and potential applications is also discussed in this review.

The telomere-to-telomere (T2T) genome of Peucedanum praeruptorum Dunn provides insights into the genome evolution and coumarin biosynthesis

BACKGROUND

Traditional Chinese medicine has used Peucedanum praeruptorum Dunn (Apiaceae) for a long time. Various coumarins, including the significant constituents praeruptorin (A-E), are the active constituents in the dried roots of P. praeruptorum. Previous transcriptomic and metabolomic studies have attempted to elucidate the distribution and biosynthetic network of these medicinal-valuable compounds. However, the lack of a high-quality reference genome impedes an in-depth understanding of genetic traits and thus the development of better breeding strategies.

RESULTS

A telomere-to-telomere (T2T) genome was assembled for P. praeruptorum by combining PacBio HiFi, ONT ultra-long, and Hi-C data. The final genome assembly was approximately 1.798 Gb, assigned to 11 chromosomes with genome completeness >98%. Comparative genomic analysis suggested that P. praeruptorum experienced 2 whole-genome duplication events. By the transcriptomic and metabolomic analysis of the coumarin metabolic pathway, we presented coumarins' spatial and temporal distribution and the expression patterns of critical genes for its biosynthesis. Notably, the COSY and cytochrome P450 genes showed tandem duplications on several chromosomes, which may be responsible for the high accumulation of coumarins.

CONCLUSIONS

A T2T genome for P. praeruptorum was obtained, providing molecular insights into the chromosomal distribution of the coumarin biosynthetic genes. This high-quality genome is an essential resource for designing engineering strategies for improving the production of these valuable compounds.

Web of venom: exploration of big data resources in animal toxin research

Research on animal venoms and their components spans multiple disciplines, including biology, biochemistry, bioinformatics, pharmacology, medicine, and more. Manipulating and analyzing the diverse array of data required for venom research can be challenging, and relevant tools and resources are often dispersed across different online platforms, making them less accessible to nonexperts. In this article, we address the multifaceted needs of the scientific community involved in venom and toxin-related research by identifying and discussing web resources, databases, and tools commonly used in this field. We have compiled these resources into a comprehensive table available on the VenomZone website (https://venomzone.expasy.org/10897). Furthermore, we highlight the challenges currently faced by researchers in accessing and using these resources and emphasize the importance of community-driven interdisciplinary approaches. We conclude by underscoring the significance of enhancing standards, promoting interoperability, and encouraging data and method sharing within the venom research community.

The rise of epitranscriptomics: recent developments and future directions

The epitranscriptomics field has undergone tremendous growth since the discovery that the RNA N6-methyladenosine (m6A) modification is reversible and is distributed throughout the transcriptome. Efforts to map RNA modifications transcriptome-wide and reshape the epitranscriptome in disease settings have facilitated mechanistic understanding and drug discovery in the field. In this review we discuss recent advancements in RNA modification detection methods and consider how these developments can be applied to gain novel insights into the epitranscriptome. We also highlight drug discovery efforts aimed at developing epitranscriptomic therapeutics for cancer and other diseases. Finally, we consider engineering of the epitranscriptome as an emerging direction to investigate RNA modifications and their causal effects on RNA processing at high specificity.

Emerging roles of RNA ac4C modification and NAT10 in mammalian development and human diseases

RNA ac4C modification is a novel and rare chemical modification observed in mRNA. Traditional biochemical studies had primarily associated ac4C modification with tRNA and rRNA until in 2018, Arango D et al. first reported the presence of ac4C modification on mRNA and demonstrated its critical role in mRNA stability and translation regulation. Furthermore, they established that the ac4C modification on mRNA is mediated by the classical N-acetyltransferase NAT10. Subsequent studies have underscored the essential implications of NAT10 and mRNA ac4C modification across both physiological and pathological regulatory processes. In this review, we aimed to explore the discovery history of RNA ac4C modification, its detection methods, and its regulatory mechanisms in disease and physiological development. We offer a forward-looking examination and discourse concerning the employment of RNA ac4C modification as a prospective therapeutic strategy across diverse diseases. Furthermore, we comprehensively summarize the functions and mechanisms of NAT10 in gene expression regulation and pathogenesis independent of RNA ac4C modification.

DNA Sequencing Technologies and DNA Barcoding

DNA barcodes are short, standardized DNA segments that geneticists can use to identify all living taxa. On the other hand, DNA barcoding identifies species by analyzing these specific regions against a DNA barcode reference library. In its initial years, DNA barcodes sequenced by Sanger's method were extensively used by taxonomists for the characterization and identification of species. But in recent years, DNA barcoding by next-generation sequencing (NGS) has found broader applications, such as quality control, biomonitoring of protected species, and biodiversity assessment. Technological advancements have also paved the way to metabarcoding, which has enabled massive parallel sequ.encing of complex bulk samples using high-throughput sequencing techniques. In future, DNA barcoding along with high-throughput techniques will show stupendous progress in taxonomic classification with reference to available sequence data.

The Use of Nanopore Sequencing to Analyze the Chloroplast Transcriptome Part II: Bioinformatic Analyzes and Virtual RNA Blots

Nanopore sequencing of full-length cDNAs offers unprecedented details of the plastid RNA metabolism. After the generation of the nanopore reads, several bioinformatic steps are required to analyze the data. In this chapter, we describe in a few simple command lines the processing and mapping of the reads as well as the generation of virtual Northern blots as a simple and familiar way to visualize Nanopore sequencing data.

Nanopore-Mediated Sequencing of Circular RNA

Circular RNAs (circRNAs) constitute a group of RNAs defined by a covalent bond between the 5' and 3' end formed by a unique back-splicing event. Most circRNAs are composed of more than one exon, which are spliced together in a linear fashion. This protocol describes methods to sequence full-length circRNA across the back-splicing junction, allowing unambiguous characterization of circRNA-specific exon-intron structures by long-read sequencing (LRS). Two different sequencing approaches are provided: (1) Global circRNA sequencing (the circNick-LRS strategy) relying on circRNA enrichment from total RNA followed by total circRNA long-read sequencing, and (2) targeted circRNA sequencing (the circPanel-LRS strategy) where a preselected panel of circRNA are sequenced without prior circRNA enrichment. Both methods were originally described in Karim et al. (Rahimi et al., Nat Commun 12: 4825, 2021) where they were applied to characterize the exon-intron structure of >10.000 circRNAs in mouse and human brains.

Next-Generation Sequencing to Study the DNA Interaction

Next-generation sequencing (NGS) has transformed genomics by allowing researchers to sequence DNA and RNA at highest speed, accuracy, and cost-effectiveness. Researchers investigate DNA interactions with the help next-generation sequencing with a great deal of information. Over the last decade, NGS technologies have advanced significantly, with the development of several platforms, including Illumina, PacBio, and Oxford Nanopore, each offering distinct advantages and uses. The use of next-generation sequencing (NGS) has aided in the discovery of genetic variations, gene expression patterns, and epigenetic modifications connected with a variety of diseases, including cancer, neurological disorders, and infectious diseases. By identifying these regions, we can control the expression of genes, cellular signaling pathways, and other key biological processes. NGS is an effective method for researching DNA interactions that has completely transformed the area of genomics. NGS has also played an important part in personalized medicine, enabling the discovery of disease-causing mutations and the creation of targeted medicines. Finally, NGS has transformed the field of genomics, resulting in new discoveries and applications in medicine, environmental sciences, and other fields.

A practical guide and Galaxy workflow to avoid inter-plasmidic repeat collapse and false gene loss in Unicycler's hybrid assemblies

Generating complete, high-quality genome assemblies is key for any downstream analysis, such as comparative genomics. For bacterial genome assembly, various algorithms and fully automated pipelines exist, which are free-of-charge and easily accessible. However, these assembly tools often cannot unambiguously resolve a bacterial genome, for example due to the presence of sequence repeat structures on the chromosome or on plasmids. Then, a more sophisticated approach and/or manual curation is needed. Such modifications can be challenging, especially for non-bioinformaticians, because they are generally not considered as a straightforward process. In this study, we propose a standardized approach for manual genome completion focusing on the popular hybrid assembly pipeline Unicycler. The provided Galaxy workflow addresses two weaknesses in Unicycler's hybrid assemblies: (i) collapse of inter-plasmidic repeats and (ii) false loss of single-copy sequences. To demonstrate and validate how to detect and resolve these assembly errors, we use two genomes from the Bacillus cereus group. By applying the proposed pipeline following an automated assembly, the genome sequence quality can be significantly improved.