scholarly journals Targeting the 16S rRNA Gene for Bacterial Identification in Complex Mixed Samples: Comparative Evaluation of Second (Illumina) and Third (Oxford Nanopore Technologies) Generation Sequencing Technologies

2019 ◽  
Vol 21 (1) ◽  
pp. 298 ◽  
Author(s):  
Raf Winand ◽  
Bert Bogaerts ◽  
Stefan Hoffman ◽  
Loïc Lefevre ◽  
Maud Delvoye ◽  
...  
Keyword(s):  
Comparative Evaluation ◽  
Species Level ◽  
Rrna Gene ◽  
Bacterial Identification ◽  
Sequencing Technologies ◽  
16S Gene ◽  
Oxford Nanopore ◽  
Oxford Nanopore Technologies ◽  
Generation Sequencing ◽  
Mixed Samples

Rapid, accurate bacterial identification in biological samples is an important task for microbiology laboratories, for which 16S rRNA gene Sanger sequencing of cultured isolates is frequently used. In contrast, next-generation sequencing does not require intermediate culturing steps and can be directly applied on communities, but its performance has not been extensively evaluated. We present a comparative evaluation of second (Illumina) and third (Oxford Nanopore Technologies (ONT)) generation sequencing technologies for 16S targeted genomics using a well-characterized reference sample. Different 16S gene regions were amplified and sequenced using the Illumina MiSeq, and analyzed with Mothur. Correct classification was variable, depending on the region amplified. Using a majority vote over all regions, most false positives could be eliminated at the genus level but not the species level. Alternatively, the entire 16S gene was amplified and sequenced using the ONT MinION, and analyzed with Mothur, EPI2ME, and GraphMap. Although >99% of reads were correctly classified at the genus level, up to ≈40% were misclassified at the species level. Both technologies, therefore, allow reliable identification of bacterial genera, but can potentially misguide identification of bacterial species, and constitute viable alternatives to Sanger sequencing for rapid analysis of mixed samples without requiring any culturing steps.

scholarly journals Benchmarking of long-read correction methods

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Juliane C Dohm ◽  
Philipp Peters ◽  
Nancy Stralis-Pavese ◽  
Heinz Himmelbauer
Keyword(s):  
Error Rate ◽  
Total Error ◽  
Error Rates ◽  
High Rate ◽  
Sequencing Technologies ◽  
Third Generation Sequencing ◽  
Oxford Nanopore ◽  
Long Read ◽  
Oxford Nanopore Technologies ◽  
Generation Sequencing

Abstract Third-generation sequencing technologies provided by Pacific Biosciences and Oxford Nanopore Technologies generate read lengths in the scale of kilobasepairs. However, these reads display high error rates, and correction steps are necessary to realize their great potential in genomics and transcriptomics. Here, we compare properties of PacBio and Nanopore data and assess correction methods by Canu, MARVEL and proovread in various combinations. We found total error rates of around 13% in the raw datasets. PacBio reads showed a high rate of insertions (around 8%) whereas Nanopore reads showed similar rates for substitutions, insertions and deletions of around 4% each. In data from both technologies the errors were uniformly distributed along reads apart from noisy 5′ ends, and homopolymers appeared among the most over-represented kmers relative to a reference. Consensus correction using read overlaps reduced error rates to about 1% when using Canu or MARVEL after patching. The lowest error rate in Nanopore data (0.45%) was achieved by applying proovread on MARVEL-patched data including Illumina short-reads, and the lowest error rate in PacBio data (0.42%) was the result of Canu correction with minimap2 alignment after patching. Our study provides valuable insights and benchmarks regarding long-read data and correction methods.

scholarly journals Haemophilus influenzae Meningitis Direct Diagnosis by Metagenomic Next-Generation Sequencing: A Case Report

Pathogens ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 461
Author(s):  
Madjid Morsli ◽  
Quentin Kerharo ◽  
Jeremy Delerce ◽  
Pierre-Hugues Roche ◽  
Lucas Troude ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Haemophilus Influenzae ◽  
Real Time ◽  
Real Time Pcr ◽  
Point Of Care ◽  
Next Generation ◽  
Oxford Nanopore ◽  
Sequence Encoding ◽  
Oxford Nanopore Technologies ◽  
Generation Sequencing

Current routine real-time PCR methods used for the point-of-care diagnosis of infectious meningitis do not allow for one-shot genotyping of the pathogen, as in the case of deadly Haemophilus influenzae meningitis. Real-time PCR diagnosed H. influenzae meningitis in a 22-year-old male patient, during his hospitalisation following a more than six-metre fall. Using an Oxford Nanopore Technologies real-time sequencing run in parallel to real-time PCR, we detected the H. influenzae genome directly from the cerebrospinal fluid sample in six hours. Furthermore, BLAST analysis of the sequence encoding for a partial DUF417 domain-containing protein diagnosed a non-b serotype, non-typeable H.influenzae belonging to lineage H. influenzae 22.1-21. The Oxford Nanopore metagenomic next-generation sequencing approach could be considered for the point-of-care diagnosis of infectious meningitis, by direct identification of pathogenic genomes and their genotypes/serotypes.

scholarly journals Picopore: A tool for reducing the storage size of Oxford Nanopore Technologies datasets without loss of functionality

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 227 ◽  
Author(s):  
Scott Gigante
Keyword(s):  
Data Storage ◽  
Data Generation ◽  
Biologically Relevant ◽  
Sequencing Technologies ◽  
Long Term Storage ◽  
Oxford Nanopore ◽  
Long Read ◽  
Oxford Nanopore Technologies ◽  
Term Storage

Oxford Nanopore Technologies' (ONT's) MinION and PromethION long-read sequencing technologies are emerging as genuine alternatives to established Next-Generation Sequencing technologies. A combination of the highly redundant file format and a rapid increase in data generation have created a significant problem both for immediate data storage on MinION-capable laptops, and for long-term storage on lab data servers. We developed Picopore, a software suite offering three methods of compression. Picopore's lossless and deep lossless methods provide a 25% and 44% average reduction in size, respectively, without removing any data from the files. Picopore's raw method provides an 88% average reduction in size, while retaining biologically relevant data for the end-user. All methods have the capacity to run in real-time in parallel to a sequencing run, reducing demand for both immediate and long-term storage space.

scholarly journals Fast-Bonito: A Faster Basecaller for Nanopore Sequencing

2020 ◽  
Author(s):  
Zhimeng Xu ◽  
Yuting Mai ◽  
Denghui Liu ◽  
Wenjun He ◽  
Xinyuan Lin ◽  
...  
Keyword(s):  
Network Architecture ◽  
Original Version ◽  
Neuron Network ◽  
Base Calling ◽  
Oxford Nanopore ◽  
Speed Up ◽  
Downstream Analysis ◽  
Next Generation Sequencing Ngs ◽  
Oxford Nanopore Technologies ◽  
Generation Sequencing

AbstractOxford Nanopore Technologies (ONT) is a promising sequencing technology that could generate relatively longer sequencing reads compared to the next generation sequencing (NGS) technology. The base calling process is very important for TGS. It translates the original electrical signals from the sequencer to the nucleotide sequence. By doing that, the base calling could significantly influence the accuracy of downstream analysis. Bonito is a recently developed basecaller based on deep neuron network, the neuron network architecture of which is composed of a single convolutional layer followed by three stacked bidirectional GRU layers. Although Bonito achieved the state-of-the-art accuracy, its speed is so slow that it is not likely to be used in production. We therefore implement Fast-Bonito, which introduces systematic optimization to speed up Bonito. Fast-Bonito archives 53.8% faster than the original version on NVIDIA V100 and could be further speed up by HUAWEI Ascend 910 NPU, achieving 565% faster than the original version. The accuracy of Fast-Bonito is also slightly higher than the original Bonito.

scholarly journals Chasing perfection: validation and polishing strategies for telomere-to-telomere genome assemblies

2021 ◽  
Author(s):  
Arang Rhie ◽  
Ann Mc Cartney ◽  
Kishwar Shafin ◽  
Michael Alonge ◽  
Andrey Bzikadze ◽  
...  
Keyword(s):  
Genome Assembly ◽  
Tandem Repeats ◽  
Hydatidiform Mole ◽  
Segmental Duplications ◽  
Sequencing Technologies ◽  
Oxford Nanopore ◽  
Human Genome Assembly ◽  
Long Read ◽  
Genome Assemblies ◽  
Oxford Nanopore Technologies

Abstract Advances in long-read sequencing technologies and genome assembly methods have enabled the recent completion of the first Telomere-to-Telomere (T2T) human genome assembly, which resolves complex segmental duplications and large tandem repeats, including centromeric satellite arrays in a complete hydatidiform mole (CHM13). Though derived from highly accurate sequencing, evaluation revealed that the initial T2T draft assembly had evidence of small errors and structural misassemblies. To correct these errors, we designed a novel repeat-aware polishing strategy that made accurate assembly corrections in large repeats without overcorrection, ultimately fixing 51% of the existing errors and improving the assembly QV to 73.9. By comparing our results to standard automated polishing tools, we outline common polishing errors and offer practical suggestions for genome projects with limited resources. We also show how sequencing biases in both PacBio HiFi and Oxford Nanopore Technologies reads cause signature assembly errors that can be corrected with a diverse panel of sequencing technologies

scholarly journals A computational strategy for rapid on-site 16S metabarcoding with Oxford Nanopore sequencing

2020 ◽  
Author(s):  
Stefano M. Marino
Keyword(s):  
Environmental Science ◽  
Nucleotide Sequencing ◽  
Rrna Gene ◽  
Computational Pipeline ◽  
Site Monitoring ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Oxford Nanopore Technologies ◽  
The 16S Rrna Gene ◽  
Computational Strategy

ABSTRACTThe investigation of microbial communities through nucleotide sequencing has become an essential asset in environmental science, not only for research oriented activities but also for on-site monitoring; one technology, in particular, holds great promises for its application directly in the field: the Oxford Nanopore Technologies (ONT) MinION sequencer is a portable and affordable device, that produces long reads, with a remarkable sequencing output (in terms of bases/hour). One of the most common approaches in microbiological investigations through sequencing is the analysis of the 16S rRNA gene, known as 16S metabarcoding. Only recently the application of MinION has extended to 16S metabarcoding; to date, a limitation is still represented by the available computational protocols: due to the intrinsic, unique features of the technology ONT long reads cannot be adequately analyzed with tools developed for previous technologies (e.g. for Illumina). In this work a computational pipeline, specifically tailored to the usage of ONT reads in 16S metabarcoding, is developed, tested and discussed. This study is particularly addressed to on site evaluations, for environmental investigations or monitoring, where running time, costs and overall efficient usage of resources are particularly important.

scholarly journals Nanopore native RNA sequencing of a human poly(A) transcriptome: RNA extraction, cDNA conversion and direct RNA and cDNA library preparation for Oxford Nanopore

2019 ◽  
Author(s):  
Rachael E. Workman ◽  
Alison D. Tang ◽  
Paul S. Tang ◽  
Miten Jain ◽  
John R. Tyson ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Rna Extraction ◽  
Human Cell Line ◽  
Cdna Libraries ◽  
Library Preparation ◽  
Sequencing Technologies ◽  
Oxford Nanopore ◽  
Sequencing Strategy ◽  
Oxford Nanopore Technologies ◽  
Cdna Library Preparation

Abstract High throughput cDNA sequencing technologies have dramatically advanced our understanding of transcriptome complexity and regulation. However, these methods lose information contained in biological RNA because the copied reads are often short and because modifications are not carried forward in cDNA. We address these limitations using a native poly(A) RNA sequencing strategy developed by Oxford Nanopore Technologies (ONT). Our study focused on poly(A) RNA from the human cell line GM12878, generating 9.9 million aligned sequence reads. These native RNA reads had an aligned N50 length of 1294 bases, and a maximum aligned length of over 21,000 bases. A total of 78,199 high-confidence isoforms were identified by combining long nanopore reads with short higher accuracy Illumina reads. We describe methods for extracting intact RNA, poly-A selection, cDNA conversion for a portion of sample, and library preparation for both direct RNA and cDNA libraries.

scholarly journals RNA Transcriptome Mapping with GraphMap

2017 ◽  
Author(s):  
Krešimir Križanović ◽  
Ivan Sović ◽  
Ivan Krpelnik ◽  
Mile Šikić
Keyword(s):  
Third Generation ◽  
Sequencing Data ◽  
Mapping Algorithm ◽  
Gene Annotations ◽  
Sequencing Technologies ◽  
Third Generation Sequencing ◽  
Oxford Nanopore ◽  
Rna Mapping ◽  
Synthetic Datasets ◽  
Generation Sequencing

AbstractNext generation sequencing technologies have made RNA sequencing widely accessible and applicable in many areas of research. In recent years, 3rd generation sequencing technologies have matured and are slowly replacing NGS for DNA sequencing. This paper presents a novel tool for RNA mapping guided by gene annotations. The tool is an adapted version of a previously developed DNA mapper – GraphMap, tailored for third generation sequencing data, such as those produced by Pacific Biosciences or Oxford Nanopore Technologies devices. It uses gene annotations to generate a transcriptome, uses a DNA mapping algorithm to map reads to the transcriptome, and finally transforms the mappings back to genome coordinates. Modified version of GraphMap is compared on several synthetic datasets to the state-of-the-art RNAseq mappers enabled to work with third generation sequencing data. The results show that our tool outperforms other tools in general mapping quality.

scholarly journals Oxford Nanopore sequencing: new opportunities for plant genomics?

2020 ◽  
Vol 71 (18) ◽  
pp. 5313-5322 ◽  
Author(s):  
Kathryn Dumschott ◽  
Maximilian H-W Schmidt ◽  
Harmeet Singh Chawla ◽  
Rod Snowdon ◽  
Björn Usadel
Keyword(s):  
Plant Genome ◽  
Third Generation ◽  
Plant Genomics ◽  
High Coverage ◽  
Plant Genomes ◽  
Sequencing Technologies ◽  
Third Generation Sequencing ◽  
Oxford Nanopore ◽  
Long Read ◽  
Generation Sequencing

Abstract DNA sequencing was dominated by Sanger’s chain termination method until the mid-2000s, when it was progressively supplanted by new sequencing technologies that can generate much larger quantities of data in a shorter time. At the forefront of these developments, long-read sequencing technologies (third-generation sequencing) can produce reads that are several kilobases in length. This greatly improves the accuracy of genome assemblies by spanning the highly repetitive segments that cause difficulty for second-generation short-read technologies. Third-generation sequencing is especially appealing for plant genomes, which can be extremely large with long stretches of highly repetitive DNA. Until recently, the low basecalling accuracy of third-generation technologies meant that accurate genome assembly required expensive, high-coverage sequencing followed by computational analysis to correct for errors. However, today’s long-read technologies are more accurate and less expensive, making them the method of choice for the assembly of complex genomes. Oxford Nanopore Technologies (ONT), a third-generation platform for the sequencing of native DNA strands, is particularly suitable for the generation of high-quality assemblies of highly repetitive plant genomes. Here we discuss the benefits of ONT, especially for the plant science community, and describe the issues that remain to be addressed when using ONT for plant genome sequencing.

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