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The use of whole genome sequencing (WGS) data generated by short-read sequencing technologies such as the Illumina sequencing platforms has been shown to provide reliable results for Salmonella serotype prediction. Emerging long-read sequencing platforms developed by Oxford Nanopore Technologies (ONT) provide an alternative WGS method to meet the needs of industry for rapid and accurate Salmonella confirmation and serotype classification. Advantages of the ONT sequencing platforms include portability, real-time base-calling and long-read sequencing. To explore whether WGS data generated by an ONT sequencing platform could accurately predict Salmonella serotypes, 38 Salmonella strains representing 34 serotypes were sequenced using R9.4 flow cells on an ONT sequencer for up to 2 h. The downstream bioinformatics analysis was performed using pipelines with different assemblers including Canu, Wdbtg2 combined with Racon, or Miniasm combined with Racon. In silico serotype prediction programs were carried out using both SeqSero2 (raw reads and genome assemblies) and SISTR (genome assemblies). The WGS data of the same strains were also obtained from Illumina Hiseq (200 x depth of coverage per genome) as a benchmark of accurate serotype prediction. Predictions using WGS data generated after 30 min, 45 min, 1 h, and 2 h of ONT sequencing time all matched the prediction results from Illumina WGS data. This study demonstrated the comparable accuracy of WGS-based serotype prediction between ONT and Illumina sequencing platforms. This study also sets a start point for future validation of ONT WGS as a rapid Salmonella confirmation and serotype classification tool for the food industry. • All 38 Salmonella strains were accurately predicted to the serotype level using whole genome sequencing data from an Oxford Nanopore sequencer • Consensus serotype prediction was obtained between nanopore and Illumina WGS data. • The turnaround time of this method from pure culture to prediction results was within one day. [ABSTRACT FROM AUTHOR]

The chromosome-centric dataset was created by applying several technologies of transcriptome profiling. The described dataset is available at NCBI repository (BioProject ID PRJNA635536). The dataset referred to the same type of tissue, cell lines, transcriptome sequencing technologies, and was accomplished in a period of 8 years (the first data were obtained in 2013 while the last ones - in 2020). The high-throughput sequencing technologies were employed along with the quantitative PCR (qPCR) approach, for data generation using the gene expression level assessment. qPCR was performed for a limited group of genes, encoded on human chromosome 18, for the Russian part of the Chromosome-Centric Human Proteome Project. The data of high-throughput sequencing are provided as Excel spreadsheets, where the data on FPKM and TMP values were evaluated for the whole transcriptome with both Illumina HiSeq and Oxford Nanopore Technologies MinION sequencing., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships which have or could be perceived to have influenced the work reported in this article., (© 2021 The Author(s). Published by Elsevier Inc.)

Background: Oxford Nanopore Technologies' instruments can sequence reads of great length. Long reads improve sequence assemblies by unambiguously spanning repetitive elements of the genome. Sequencing reads of significant length requires the preservation of long DNA template molecules through library preparation by pipetting reagents as slowly as possible to minimize shearing. This process is time-consuming and inconsistent at preserving read length as even small changes in volumetric flow rate can result in template shearing., Results: We have designed SNAILS (Slow Nucleic Acid Instrument for Long Sequences), a 3D-printable instrument that automates slow pipetting of reagents used in long read library preparation for Oxford Nanopore sequencing. Across six sequencing libraries, SNAILS preserved more reads exceeding 100 kilobases in length and increased its libraries' average read length over manual slow pipetting., Conclusions: SNAILS is a low-cost, easily deployable solution for improving sequencing projects that require reads of significant length. By automating the slow pipetting of library preparation reagents, SNAILS increases the consistency and throughput of long read Nanopore sequencing.

The use of whole genome sequencing (WGS) data generated by the long-read sequencing platform Oxford Nanopore Technologies (ONT) has been shown to provide reliable results for Salmonella serotype prediction in a previous study. To further meet the needs of industry for accurate, rapid, and cost-efficient Salmonella confirmation and serotype classification, we evaluated the serotype prediction accuracy of using WGS data from multiplex ONT sequencing with three, four, five, seven, or ten Salmonella isolates (each isolate represented one Salmonella serotype) pooled in one R9.4.1 flow cell. Each multiplexing strategy was repeated with five flow cells, and the loaded samples were sequenced simultaneously in a GridION sequencer for 48 h. In silico serotype prediction was performed using both SeqSero2 (for raw reads and genome assemblies) and SISTR (for genome assemblies) software suites. An average of 10.63 Gbp of clean sequencing data was obtained per flow cell. We found that the unevenness of data yield among each multiplexed isolate was a major barrier for shortening sequencing time. Using genome assemblies, both SeqSero2 and SISTR accurately predicted all the multiplexed isolates under each multiplexing strategy when depth of genome coverage ≥50× for each isolate. We identified that cross-sample barcode assignment was a major cause of prediction errors when raw sequencing data were used for prediction. This study also demonstrated that, (i) sequence data generated by ONT multiplex sequencing can be used to simultaneously predict serotype for three to ten Salmonella isolates, (ii) with three to ten Salmonella isolates multiplexed, genome coverage at ≥50× per isolate was obtained within an average of 6 h of ONT multiplex sequencing, and (iii) with five isolates multiplexed, the cost per isolate might be reduced to 23% of that incurred with single ONT sequencing. This study is a starting point for future validation of multiplex ONT WGS as a cost-efficient and rapid Salmonella confirmation and serotype classification tool for the food industry., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Wu, Luo, Xu, Ge, Li, Deng, Wiedmann, Baker, Stevenson, Zhang and Tang.)

Recent years have seen great progresses in third-generation sequencing. New commercial platforms from Oxford Nanopore Technologies (ONT) can generate ultra-long reads from single-molecule nucleic acid fragments of kilobases up to megabases, exceeding the limitation of short reads and dependency on template amplification suffered by the previous generation of sequencing technologies. Moreover, it can detect epigenetic modifications directly, as well as providing all-around field usage, being pocket-sized and low cost. It has already been applied to yeast research in many aspects, such as complete de novo genome assemblies, the phylogeny of large-brewing yeasts, gene isoform identification, and base modification detection. These applications have delivered novel insights into yeast genomic and transcriptomic analysis.

Due to highly repetitive genome sequences, short-read-based Trypanosoma cruzi genomes are extremely fragmented. Contiguous trypanosomatid genomes assemblies have resulted in the advent of third-generation sequencing technologies. Long reads span several to hundreds of kbps allowing to correct assemblies of repeated and low complexity DNA regions. However, these techniques present higher error rates. Hybrid assembly strategies that combine error-prone long reads with much more accurate Illumina short reads represent a very convenient approach for enhancing genome completeness. Here, we describe how to perform a hybrid assembly for genomic analysis of protozoan pathogens using Illumina and Oxford Nanopore sequencing., (© 2021. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

RNA modifications play pivotal roles in the RNA life cycle and RNA fate, and are now appreciated as a major posttranscriptional regulatory layer in the cell. In the last few years, direct RNA nanopore sequencing (dRNA-seq) has emerged as a promising technology that can provide single-molecule resolution maps of RNA modifications in their native RNA context. While native RNA can be successfully sequenced using this technology, the detection of RNA modifications is still challenging. Here, we provide an upgraded version of EpiNano (version 1.2), an algorithm to predict m 6 A RNA modifications from dRNA-seq datasets. The latest version of EpiNano contains models for predicting m 6 A RNA modifications in dRNA-seq data that has been base-called with Guppy. Moreover, it can now train models with features extracted from both base-called dRNA-seq FASTQ data and raw FAST5 nanopore outputs. Finally, we describe how EpiNano can be used in stand-alone mode to extract base-calling "error" features and current intensity information from dRNA-seq datasets. In this chapter, we provide step-by-step instructions on how to produce in vitro transcribed constructs to train EpiNano, as well as detailed information on how to use EpiNano to train, test, and predict m 6 A RNA modifications in dRNA-seq data.

Background: Sequencing technologies have advanced to the point where it is possible to generate high-accuracy, haplotype-resolved, chromosome-scale assemblies. Several long-read sequencing technologies are available, and a growing number of algorithms have been developed to assemble the reads generated by those technologies. When starting a new genome project, it is therefore challenging to select the most cost-effective sequencing technology, as well as the most appropriate software for assembly and polishing. It is thus important to benchmark different approaches applied to the same sample., Results: Here, we report a comparison of 3 long-read sequencing technologies applied to the de novo assembly of a plant genome, Macadamia jansenii. We have generated sequencing data using Pacific Biosciences (Sequel I), Oxford Nanopore Technologies (PromethION), and BGI (single-tube Long Fragment Read) technologies for the same sample. Several assemblers were benchmarked in the assembly of Pacific Biosciences and Nanopore reads. Results obtained from combining long-read technologies or short-read and long-read technologies are also presented. The assemblies were compared for contiguity, base accuracy, and completeness, as well as sequencing costs and DNA material requirements., Conclusions: The 3 long-read technologies produced highly contiguous and complete genome assemblies of M. jansenii. At the time of sequencing, the cost associated with each method was significantly different, but continuous improvements in technologies have resulted in greater accuracy, increased throughput, and reduced costs. We propose updating this comparison regularly with reports on significant iterations of the sequencing technologies., (© The Author(s) 2020. Published by Oxford University Press GigaScience.)

Background: Long-read sequencing is increasingly being used to determine eukaryotic genomes. We used nanopore technology to generate chromosome-level assemblies for 3 different strains of Drechmeria coniospora, a nematophagous fungus used extensively in the study of innate immunity in Caenorhabditis elegans., Results: One natural geographical isolate demonstrated high stability over decades, whereas a second isolate not only had a profoundly altered genome structure but exhibited extensive instability. We conducted an in-depth analysis of sequence errors within the 3 genomes and established that even with state-of-the-art tools, nanopore methods alone are insufficient to generate eukaryotic genome sequences of sufficient accuracy to merit inclusion in public databases., Conclusions: Although nanopore long-read sequencing is not accurate enough to produce publishable eukaryotic genomes, in our case, it has revealed new information about genome plasticity in D. coniospora and provided a backbone that will permit future detailed study to characterize gene evolution in this important model fungal pathogen., (© The Author(s) 2020. Published by Oxford University Press GigaScience.)

Recent advances in genome sequencing technologies have simplified the generation of genome data and reduced the costs for genome assemblies, even for complex genomes like those of vertebrates. More practically oriented genomic courses can prepare university students for the increasing importance of genomic data used in biological and medical research. Low-cost third-generation sequencing technology, along with publicly available data, can be used to teach students how to process genomic data, assemble full chromosome-level genomes, and publish the results in peer-reviewed journals, or preprint servers. Here we outline experiences gained from 2 master's-level courses and discuss practical considerations for teaching hands-on genome assembly courses., (© The Author(s) 2020. Published by Oxford University Press.)

A Gram-negative rod from the Yersinia genus was isolated from a clinical case of yersiniosis in the United Kingdom. Long read sequencing data from an Oxford Nanopore Technologies (ONT) MinION in conjunction with Illumina HiSeq reads were used to generate a finished quality genome of this strain. Overall Genome Related Index (OGRI) of the strain was used to determine that it was a novel species within Yersinia , despite biochemical similarities to Yersinia enterocolitica . The 16S ribosomal RNA gene accessions are MN434982-MN434987 and the accession number for the complete and closed chromosome is CP043727. The type strain is SRR7544370 T (=NCTC 14382 T /=LMG 31573 T ).

Background:  Data sets from long-read sequencing platforms (Oxford Nanopore Technologies and Pacific Biosciences) allow for most prokaryote genomes to be completely assembled - one contig per chromosome or plasmid. However, the high per-read error rate of long-read sequencing necessitates different approaches to assembly than those used for short-read sequencing. Multiple assembly tools (assemblers) exist, which use a variety of algorithms for long-read assembly. Methods:  We used 500 simulated read sets and 120 real read sets to assess the performance of six long-read assemblers (Canu, Flye, Miniasm/Minipolish, Raven, Redbean and Shasta) across a wide variety of genomes and read parameters. Assemblies were assessed on their structural accuracy/completeness, sequence identity, contig circularisation and computational resources used. Results:  Canu v1.9 produced moderately reliable assemblies but had the longest runtimes of all assemblers tested. Flye v2.6 was more reliable and did particularly well with plasmid assembly. Miniasm/Minipolish v0.3 was the only assembler which consistently produced clean contig circularisation. Raven v0.0.5 was the most reliable for chromosome assembly, though it did not perform well on small plasmids and had circularisation issues. Redbean v2.5 and Shasta v0.3.0 were computationally efficient but more likely to produce incomplete assemblies. Conclusions:  Of the assemblers tested, Flye, Miniasm/Minipolish and Raven performed best overall. However, no single tool performed well on all metrics, highlighting the need for continued development on long-read assembly algorithms., Competing Interests: No competing interests were disclosed., (Copyright: © 2019 Wick RR and Holt KE.)

Background Poxviruses are large DNA viruses that infect humans and animals. Vaccinia virus (VACV) has been applied as a live vaccine for immunization against smallpox, which was eradicated by 1980 as a result of worldwide vaccination. VACV is the prototype of poxviruses in the investigation of the molecular pathogenesis of the virus. Short-read sequencing methods have revolutionized transcriptomics; however, they are not efficient in distinguishing between the RNA isoforms and transcript overlaps. Long-read sequencing (LRS) is much better suited to solve these problems and also allow direct RNA sequencing. Despite the scientific relevance of VACV, no LRS data have been generated for the viral transcriptome to date. Findings For the deep characterization of the VACV RNA profile, various LRS platforms and library preparation approaches were applied. The raw reads were mapped to the VACV reference genome and also to the host (Chlorocebus sabaeus) genome. In this study, we applied the Pacific Biosciences RSII and Sequel platforms, which altogether resulted in 937,531 mapped reads of inserts (1.42 Gb), while we obtained 2,160,348 aligned reads (1.75 Gb) from the different library preparation methods using the MinION device from Oxford Nanopore Technologies. Conclusions By applying cutting-edge technologies, we were able to generate a large dataset that can serve as a valuable resource for the investigation of the dynamic VACV transcriptome, the virus-host interactions, and RNA base modifications. These data can provide useful information for novel gene annotations in the VACV genome. Our dataset can also be used to analyze the currently available LRS platforms, library preparation methods, and bioinformatics pipelines. [ABSTRACT FROM AUTHOR]

Transcriptome studies evaluating whole blood and tissues are often confounded by overrepresentation of highly abundant transcripts. These abundant transcripts are problematic, as they compete with and prevent the detection of rare RNA transcripts, obscuring their biological importance. This issue is more pronounced when using long-read sequencing technologies for isoform-level transcriptome analysis, as they have relatively lower throughput compared to short-read sequencers. As a result, long-read based transcriptome analysis is prohibitively expensive for non-model organisms. While there are off-the-shelf kits available for select model organisms capable of depleting highly abundant transcripts for alpha (HBA) and beta (HBB) hemoglobin, they are unsuitable for non-model organisms. To address this, we have adapted the recent CRISPR/Cas9-based depletion method (depletion of abundant sequences by hybridization) for long-read full-length cDNA sequencing approaches that we call Long-DASH. Using a recombinant Cas9 protein with appropriate guide RNAs, full-length hemoglobin transcripts can be depleted in vitro prior to performing any short- and long-read sequencing library preparations. Using this method, we sequenced depleted full-length cDNA in parallel using both our Oxford Nanopore Technology (ONT) based R2C2 long-read approach, as well as the Illumina short-read based Smart-seq2 approach. To showcase this, we have applied our methods to create an isoform-level transcriptome from whole blood samples derived from three polar bears ( Ursus maritimus ). Using Long-DASH, we succeeded in depleting hemoglobin transcripts and generated deep Smart-seq2 Illumina datasets and 3.8 million R2C2 full-length cDNA consensus reads. Applying Long-DASH with our isoform identification pipeline, Mandalorion, we discovered ∼6,000 high-confidence isoforms and a number of novel genes. This indicates that there is a high diversity of gene isoforms within U. maritimus not yet reported. This reproducible and straightforward approach has not only improved the polar bear transcriptome annotations but will serve as the foundation for future efforts to investigate transcriptional dynamics within the 19 polar bear subpopulations around the Arctic.

A Gram-stain-negative, rod-shaped strain isolated from pig-production environments was identified as a new species within the genus Yersinia using multifaceted genomic and biochemical approaches. The genome of this strain was closed using a hybrid assembly approach combining both high accuracy short read sequencing data with long read sequencing technology. Phylogenetic analysis of the 16S rRNA gene showed ~98 % similarity to Yersinia kristensenii and ~98 % similarity to Yersinia enterocolitica. Average nucleotide identity (OrthoANI) values were calculated as 85.79 % to Y. kristensenii ATCC 33638 T and 85.73 % to Y. enterocolitica ATCC 9610 T thereby providing evidence that this isolate should be considered as a novel species. The type strain is CFS1934 T (=NCTC 14222 T =LMG 31076 T ).

Background: In light of the current biodiversity crisis, DNA barcoding is developing into an essential tool to quantify state shifts in global ecosystems. Current barcoding protocols often rely on short amplicon sequences, which yield accurate identification of biological entities in a community but provide limited phylogenetic resolution across broad taxonomic scales. However, the phylogenetic structure of communities is an essential component of biodiversity. Consequently, a barcoding approach is required that unites robust taxonomic assignment power and high phylogenetic utility. A possible solution is offered by sequencing long ribosomal DNA (rDNA) amplicons on the MinION platform (Oxford Nanopore Technologies)., Findings: Using a dataset of various animal and plant species, with a focus on arthropods, we assemble a pipeline for long rDNA barcode analysis and introduce a new software (MiniBar) to demultiplex dual indexed Nanopore reads. We find excellent phylogenetic and taxonomic resolution offered by long rDNA sequences across broad taxonomic scales. We highlight the simplicity of our approach by field barcoding with a miniaturized, mobile laboratory in a remote rainforest. We also test the utility of long rDNA amplicons for analysis of community diversity through metabarcoding and find that they recover highly skewed diversity estimates., Conclusions: Sequencing dual indexed, long rDNA amplicons on the MinION platform is a straightforward, cost-effective, portable, and universal approach for eukaryote DNA barcoding. Although bulk community analyses using long-amplicon approaches may introduce biases, the long rDNA amplicons approach signifies a powerful tool for enabling the accurate recovery of taxonomic and phylogenetic diversity across biological communities., (© The Author(s) 2019. Published by Oxford University Press.)

Despite the ever increase in rigorous control and monitoring measures to assure safe food along the entire farm-to-fork chain, the past decade has also witnessed an increase in microbial food alerts. Hence, research on food safety and quality remain of utmost importance. Complementary, and at least as important, is the necessity to be able to assess the potential microbial risks along the food chain. Risk assessment relies on sound scientific data. Unfortunately, often, quality data are limited if not lacking. High-throughput tools such as next-generation sequencing (NGS) could fill this gap. NGS approaches can be used to generate ample qualitative and quantitative data to be used in the risk assessment process. NGS applications are not new in food microbiology with applications ranging from pathogen detection along the food chain, food epidemiology studies, whole genome analysis of food-associated microorganisms up to describing complete food microbiomes. Yet, its application in the area of microbial risk assessment is still at an early stage and faces important challenges. The possibilities of NGS for risk assessment are ample, but so are the questions on the subject. One of the major strengths of NGS lies in its capacity to generate a lot of data, but to what extend can this wealth be of use in hazard identification, hazard characterisation and exposure assessment to perform a sound risk characterisation, which in turn will make it possible to take substantiated risk management decisions., (© 2018 European Food Safety Authority. EFSA Journal published by John Wiley and Sons Ltd on behalf of European Food Safety Authority.)

A better understanding of the genomic changes that facilitate the emergence and spread of drug-resistant Mycobacterium tuberculosis strains is currently required. Here, we report the use of the MinION nanopore sequencer (Oxford Nanopore Technologies) to sequence and assemble an extensively drug-resistant (XDR) isolate, which is part of a modern Beijing sub-lineage strain, prevalent in Western Province, Papua New Guinea. Using 238-fold coverage obtained from a single flow-cell, de novo assembly of nanopore reads resulted into one contiguous assembly with 99.92 % assembly accuracy. Incorporation of complementary short read sequences (Illumina) as part of consensus error correction resulted in a 4 404 064 bp genome with 99.98 % assembly accuracy. This assembly had an average nucleotide identity of 99.7 % relative to the reference genome, H37Rv. We assembled nearly all GC-rich repetitive PE/PPE family genes (166/168) and identified variants within these genes. With an estimated genotypic error rate of 5.3 % from MinION data, we demonstrated identification of variants to include the conventional drug resistance mutations, and those that contribute to the resistance phenotype (efflux pumps/transporter) and virulence. Reference-based alignment of the assembly allowed detection of deletions and insertions. MinION sequencing provided a fully annotated assembly of a transmissible XDR strain from an endemic setting and showed its utility to provide further understanding of genomic processes within Mycobacterium tuberculosis.

Background: Given the demonstrated utility of Third Generation Sequencing [Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT)] long reads in many studies, a comprehensive analysis and comparison of their data quality and applications is in high demand. Methods: Based on the transcriptome sequencing data from human embryonic stem cells, we analyzed multiple data features of PacBio and ONT, including error pattern, length, mappability and technical improvements over previous platforms. We also evaluated their application to transcriptome analyses, such as isoform identification and quantification and characterization of transcriptome complexity, by comparing the performance of PacBio, ONT and their corresponding Hybrid-Seq strategies (PacBio+Illumina and ONT+Illumina). Results: PacBio shows overall better data quality, while ONT provides a higher yield. As with data quality, PacBio performs marginally better than ONT in most aspects for both long reads only and Hybrid-Seq strategies in transcriptome analysis. In addition, Hybrid-Seq shows superior performance over long reads only in most transcriptome analyses. Conclusions: Both PacBio and ONT sequencing are suitable for full-length single-molecule transcriptome analysis. As this first use of ONT reads in a Hybrid-Seq analysis has shown, both PacBio and ONT can benefit from a combined Illumina strategy. The tools and analytical methods developed here provide a resource for future applications and evaluations of these rapidly-changing technologies., Competing Interests: Competing interests: No competing interests were disclosed.