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 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.

PSXIV-24 Real-time, on-site whole genome sequencing with oxford nanopore technologies’ MinION

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 257-258
Author(s):  
Hanna Ostrovski ◽  
Rodrigo Pelicioni Savegnago ◽  
Wen Huang ◽  
Cedric Gondro
Keyword(s):  
Real Time ◽  
Ease Of Use ◽  
Whole Genome Sequence ◽  
Genomic Sequencing ◽  
Whole Genome ◽  
Illumina Hiseq ◽  
Base Calling ◽  
Oxford Nanopore ◽  
Oxford Nanopore Technologies

Abstract Most quantitative geneticists are traditionally trained for data analysis in genetic evaluation and genomic prediction, but rarely have extensive knowledge of molecular genetics or experience in experimental labs. Recent products, such as those launched by Oxford Nanopore Technologies (ONT), give those quantitative geneticists a comprehensible and hands-on toolkit to explore DNA sequencing. The ‘MinION’, a small DNA sequencer, is of interest for quantitative geneticists due to both the minimal learning curve and the non-proprietary USB connectivity. This device is small enough to be portable, allowing for potential real-time, on-farm sequencing. The objective of this project is to compare the whole genome sequence (WGS) output of the MinION sequencer to that of the Illumina HiSeq 4000. Blood was collected from a 6-month-old Akaushi calf born on a Michigan State University farm. DNA was extracted from the sample using the QIAamp DNA Blood Kit from Qiagen, and library DNA ligation preparation (SQK-LSK109) from ONT was used. After base-calling with guppy software (provided by ONT), the data were preprocessed and experimental runs with the MinION were compared using quality control. Finally, the data were aligned with guppy software, and was compared to the aligned WGS obtained with Illumina HiSeq. Quality results from each MinION indicate that, despite the low amount of sequence collected in each run (~225,303 reads per run), the quality of bases sequenced was high (Q≥7). The aligned data from the Illumina sequencer provided 40x coverage of the genome, with a total of 739,339,742 reads. Although the amount of data obtained with MinION is much smaller than that of Illumina HiSeq, the high quality of MinION’s data combined with its ease of use give an opportunity of genomic sequencing for users who are either inexperienced or do not have access to large genomic sequencing devices.

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 Demystification of RNAseq Quality Control

2021 ◽  
Vol 22 (2) ◽  
Author(s):  
Dragana Dudić ◽  
Bojana Banović Đeri ◽  
Vesna Pajić ◽  
Gordana Pavlović-Lažetić
Keyword(s):  
Quality Control ◽  
Next Generation Sequencing ◽  
Rna Sequencing ◽  
Next Generation ◽  
Comprehensive Guidance ◽  
Dna And Rna ◽  
Control Evaluation ◽  
Downstream Analysis ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing

Next Generation Sequencing (NGS) analysis has become a widely used method for studying the structure of DNA and RNA, but complexity of the procedure leads to obtaining error-prone datasets which need to be cleansed in order to avoid misinterpretation of data. We address the usage and proper interpretations of characteristic metrics for RNA sequencing (RNAseq) quality control, implemented in and reported by FastQC, and provide a comprehensive guidance for their assessment in the context of total RNAseq quality control of Illumina raw reads. Additionally, we give recommendations how to adequately perform the quality control preprocessing step of raw total RNAseq Illumina reads according to the obtained results of the quality control evaluation step; the aim is to provide the best dataset to downstream analysis, rather than to get better FastQC results. We also tested effects of different preprocessing approaches to the downstream analysis and recommended the most suitable approach.

scholarly journals Accurate detection of m6A RNA modifications in native RNA sequences

2019 ◽  
Author(s):  
Huanle Liu ◽  
Oguzhan Begik ◽  
Morghan C Lucas ◽  
Christopher E. Mason ◽  
Schraga Schwartz ◽  
...  
Keyword(s):  
Rna Modifications ◽  
Rna Sequences ◽  
Single Nucleotide ◽  
Rna Molecules ◽  
Base Calling ◽  
Oxford Nanopore ◽  
Nucleotide Resolution ◽  
The Universe ◽  
Oxford Nanopore Technologies ◽  
Single Nucleotide Resolution

ABSTRACTThe field of epitranscriptomics has undergone an enormous expansion in the last few years; however, a major limitation is the lack of generic methods to map RNA modifications transcriptome-wide. Here we show that using Oxford Nanopore Technologies, N6-methyladenosine (m6A) RNA modifications can be detected with high accuracy, in the form of systematic errors and decreased base-calling qualities. Our results open new avenues to investigate the universe of RNA modifications with single nucleotide resolution, in individual RNA molecules.

scholarly journals LongQC: A Quality Control Tool for Third Generation Sequencing Long Read Data

2020 ◽  
Vol 10 (4) ◽  
pp. 1193-1196
Author(s):  
Yoshinori Fukasawa ◽  
Luca Ermini ◽  
Hai Wang ◽  
Karen Carty ◽  
Min-Sin Cheung
Keyword(s):  
Quality Control ◽  
Third Generation ◽  
Third Generation Sequencing ◽  
Oxford Nanopore ◽  
Quality Control Tool ◽  
Long Read ◽  
Automated Quality Control ◽  
Oxford Nanopore Technologies ◽  
Generation Sequencing ◽  
Control Tool

We propose LongQC as an easy and automated quality control tool for genomic datasets generated by third generation sequencing (TGS) technologies such as Oxford Nanopore technologies (ONT) and SMRT sequencing from Pacific Bioscience (PacBio). Key statistics were optimized for long read data, and LongQC covers all major TGS platforms. LongQC processes and visualizes those statistics automatically and quickly.

scholarly journals Relative Performance of MinION (Oxford Nanopore Technologies) versus Sequel (Pacific Biosciences) Third-Generation Sequencing Instruments in Identification of Agricultural and Forest Fungal Pathogens

2019 ◽  
Vol 85 (21) ◽  
Author(s):  
Kaire Loit ◽  
Kalev Adamson ◽  
Mohammad Bahram ◽  
Rasmus Puusepp ◽  
Sten Anslan ◽  
...  
Keyword(s):  
Dna Extraction ◽  
Molecular Identification ◽  
Error Rate ◽  
Third Generation ◽  
High Error Rate ◽  
Pacific Biosciences ◽  
Third Generation Sequencing ◽  
Oxford Nanopore ◽  
Oxford Nanopore Technologies ◽  
Generation Sequencing

ABSTRACT Culture-based molecular identification methods have revolutionized detection of pathogens, yet these methods are slow and may yield inconclusive results from environmental materials. The second-generation sequencing tools have much-improved precision and sensitivity of detection, but these analyses are costly and may take several days to months. Of the third-generation sequencing techniques, the portable MinION device (Oxford Nanopore Technologies) has received much attention because of its small size and possibility of rapid analysis at reasonable cost. Here, we compare the relative performances of two third-generation sequencing instruments, MinION and Sequel (Pacific Biosciences), in identification and diagnostics of fungal and oomycete pathogens from conifer (Pinaceae) needles and potato (Solanum tuberosum) leaves and tubers. We demonstrate that the Sequel instrument is efficient for metabarcoding of complex samples, whereas MinION is not suited for this purpose due to a high error rate and multiple biases. However, we find that MinION can be utilized for rapid and accurate identification of dominant pathogenic organisms and other associated organisms from plant tissues following both amplicon-based and PCR-free metagenomics approaches. Using the metagenomics approach with shortened DNA extraction and incubation times, we performed the entire MinION workflow, from sample preparation through DNA extraction, sequencing, bioinformatics, and interpretation, in 2.5 h. We advocate the use of MinION for rapid diagnostics of pathogens and potentially other organisms, but care needs to be taken to control or account for multiple potential technical biases. IMPORTANCE Microbial pathogens cause enormous losses to agriculture and forestry, but current combined culturing- and molecular identification-based detection methods are too slow for rapid identification and application of countermeasures. Here, we develop new and rapid protocols for Oxford Nanopore MinION-based third-generation diagnostics of plant pathogens that greatly improve the speed of diagnostics. However, due to high error rate and technical biases in MinION, the Pacific BioSciences Sequel platform is more useful for in-depth amplicon-based biodiversity monitoring (metabarcoding) from complex environmental samples.

scholarly journals Comprehensive Wet-Bench and Bioinformatics Workflow for Complex Microbiota Using Oxford Nanopore Technologies

mSystems ◽  
2021 ◽  
Author(s):  
Christoph Ammer-Herrmenau ◽  
Nina Pfisterer ◽  
Tim van den Berg ◽  
Ivana Gavrilova ◽  
Ahmad Amanzada ◽  
...  
Keyword(s):  
Dna Sequencing ◽  
Real Time ◽  
Dna Fragments ◽  
Microbiome Analysis ◽  
Oxford Nanopore ◽  
Oxford Nanopore Technologies ◽  
Generation Sequencing ◽  
Bioinformatics Workflow

Advanced microbiome analysis relies on sequencing of short DNA fragments from microorganisms like bacteria, fungi, and viruses. More recently, long fragment DNA sequencing of 3rd generation sequencing has gained increasing importance and can be rapidly conducted within a few hours due to its potential real-time sequencing.

scholarly journals MSRCall: A Multi-scale Deep Neural Network to Basecall Oxford Nanopore Sequences

2021 ◽  
Author(s):  
Yang-Ming Yeh ◽  
Yi-Chang Lu
Keyword(s):  
Neural Network ◽  
Network Architecture ◽  
Ionic Current ◽  
Scale Structure ◽  
Neural Network Architecture ◽  
Translation Process ◽  
Multi Scale ◽  
Oxford Nanopore ◽  
Rna Fragments ◽  
Oxford Nanopore Technologies

MinION, a third-generation sequencer from Oxford Nanopore Technologies, is a portable device that can provide long nucleotide read data in real-time. It primarily aims to deduce the makeup of nucleotide sequences from the ionic current signals generated when passing DNA/RNA fragments through nanopores charged with a voltage difference. To determine the nucleotides from the measured signals, a translation process known as basecalling is required. However, compared to NGS basecallers, the calling accuracy of MinION still needs to be improved. In this work, a simple but powerful neural network architecture called MSRCall is proposed. MSRCall comprises a multi-scale structure, recurrent layers, a fusion block, and a CTC decoder. To better identify both short-range and long-range dependencies, the recurrent layer is redesigned to capture various time-scale features with a multi-scale structure. The results show that MSRCall outperforms other basecallers in terms of both read and consensus accuracies.

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