scholarly journals Benchmarking Long-Read Assemblers for Genomic Analyses of Bacterial Pathogens Using Oxford Nanopore Sequencing

2020 ◽  
Vol 21 (23) ◽  
pp. 9161
Author(s):  
Zhao Chen ◽  
David L. Erickson ◽  
Jianghong Meng
Keyword(s):  
Virulence Genes ◽  
Bacterial Pathogens ◽  
Error Rates ◽  
Nanopore Sequencing ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Genomic Analyses ◽  
Long Read ◽  
Genome Analyses ◽  
Assembly Algorithms

Oxford Nanopore sequencing can be used to achieve complete bacterial genomes. However, the error rates of Oxford Nanopore long reads are greater compared to Illumina short reads. Long-read assemblers using a variety of assembly algorithms have been developed to overcome this deficiency, which have not been benchmarked for genomic analyses of bacterial pathogens using Oxford Nanopore long reads. In this study, long-read assemblers, namely Canu, Flye, Miniasm/Racon, Raven, Redbean, and Shasta, were thus benchmarked using Oxford Nanopore long reads of bacterial pathogens. Ten species were tested for mediocre- and low-quality simulated reads, and 10 species were tested for real reads. Raven was the most robust assembler, obtaining complete and accurate genomes. All Miniasm/Racon and Raven assemblies of mediocre-quality reads provided accurate antimicrobial resistance (AMR) profiles, while the Raven assembly of Klebsiella variicola with low-quality reads was the only assembly with an accurate AMR profile among all assemblers and species. All assemblers functioned well for predicting virulence genes using mediocre-quality and real reads, whereas only the Raven assemblies of low-quality reads had accurate numbers of virulence genes. Regarding multilocus sequence typing (MLST), Miniasm/Racon was the most effective assembler for mediocre-quality reads, while only the Raven assemblies of Escherichia coli O157:H7 and K. variicola with low-quality reads showed positive MLST results. Miniasm/Racon and Raven were the best performers for MLST using real reads. The Miniasm/Racon and Raven assemblies showed accurate phylogenetic inference. For the pan-genome analyses, Raven was the strongest assembler for simulated reads, whereas Miniasm/Racon and Raven performed the best for real reads. Overall, the most robust and accurate assembler was Raven, closely followed by Miniasm/Racon.

scholarly journals Benchmarking hybrid assembly approaches for genomic analyses of bacterial pathogens using Illumina and Oxford Nanopore sequencing

BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhao Chen ◽  
David L. Erickson ◽  
Jianghong Meng
Keyword(s):  
Virulence Genes ◽  
Reference Genome ◽  
Bacterial Pathogens ◽  
Nanopore Sequencing ◽  
Hybrid Assembly ◽  
Pan Genome ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Hybrid Assemblies ◽  
Reference Genomes

Abstract Background We benchmarked the hybrid assembly approaches of MaSuRCA, SPAdes, and Unicycler for bacterial pathogens using Illumina and Oxford Nanopore sequencing by determining genome completeness and accuracy, antimicrobial resistance (AMR), virulence potential, multilocus sequence typing (MLST), phylogeny, and pan genome. Ten bacterial species (10 strains) were tested for simulated reads of both mediocre- and low-quality, whereas 11 bacterial species (12 strains) were tested for real reads. Results Unicycler performed the best for achieving contiguous genomes, closely followed by MaSuRCA, while all SPAdes assemblies were incomplete. MaSuRCA was less tolerant of low-quality long reads than SPAdes and Unicycler. The hybrid assemblies of five antimicrobial-resistant strains with simulated reads provided consistent AMR genotypes with the reference genomes. The MaSuRCA assembly of Staphylococcus aureus with real reads contained msr(A) and tet(K), while the reference genome and SPAdes and Unicycler assemblies harbored blaZ. The AMR genotypes of the reference genomes and hybrid assemblies were consistent for the other five antimicrobial-resistant strains with real reads. The numbers of virulence genes in all hybrid assemblies were similar to those of the reference genomes, irrespective of simulated or real reads. Only one exception existed that the reference genome and hybrid assemblies of Pseudomonas aeruginosa with mediocre-quality long reads carried 241 virulence genes, whereas 184 virulence genes were identified in the hybrid assemblies of low-quality long reads. The MaSuRCA assemblies of Escherichia coli O157:H7 and Salmonella Typhimurium with mediocre-quality long reads contained 126 and 118 virulence genes, respectively, while 110 and 107 virulence genes were detected in their MaSuRCA assemblies of low-quality long reads, respectively. All approaches performed well in our MLST and phylogenetic analyses. The pan genomes of the hybrid assemblies of S. Typhimurium with mediocre-quality long reads were similar to that of the reference genome, while SPAdes and Unicycler were more tolerant of low-quality long reads than MaSuRCA for the pan-genome analysis. All approaches functioned well in the pan-genome analysis of Campylobacter jejuni with real reads. Conclusions Our research demonstrates the hybrid assembly pipeline of Unicycler as a superior approach for genomic analyses of bacterial pathogens using Illumina and Oxford Nanopore sequencing.

scholarly journals Fast and sensitive mapping of error-prone nanopore sequencing reads with GraphMap

2015 ◽  
Author(s):  
Ivan Sovic ◽  
Mile Sikic ◽  
Andreas Wilm ◽  
Shannon Nicole Fenlon ◽  
Swaine Chen ◽  
...  
Keyword(s):  
Human Genome ◽  
Variant Calling ◽  
Error Rates ◽  
Nanopore Sequencing ◽  
Structural Variants ◽  
Specific Identification ◽  
Long Reads ◽  
Long Read ◽  
Specific Error ◽  
Very High

Exploiting the power of nanopore sequencing requires the development of new bioinformatics approaches to deal with its specific error characteristics. We present the first nanopore read mapper (GraphMap) that uses a read-funneling paradigm to robustly handle variable error rates and fast graph traversal to align long reads with speed and very high precision (>95%). Evaluation on MinION sequencing datasets against short and long-read mappers indicates that GraphMap increases mapping sensitivity by at least 15-80%. GraphMap alignments are the first to demonstrate consensus calling with <1 error in 100,000 bases, variant calling on the human genome with 76% improvement in sensitivity over the next best mapper (BWA-MEM), precise detection of structural variants from 100bp to 4kbp in length and species and strain-specific identification of pathogens using MinION reads. GraphMap is available open source under the MIT license at https://github.com/isovic/graphmap.

scholarly journals Evaluation of Germline Structural Variant Calling Methods for Nanopore Sequencing Data

2021 ◽  
Vol 12 ◽  
Author(s):  
Davide Bolognini ◽  
Alberto Magi
Keyword(s):  
Variant Calling ◽  
Research Report ◽  
Nanopore Sequencing ◽  
Sequencing Data ◽  
Factors Affecting ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Sequencing Studies ◽  
Long Read

Structural variants (SVs) are genomic rearrangements that involve at least 50 nucleotides and are known to have a serious impact on human health. While prior short-read sequencing technologies have often proved inadequate for a comprehensive assessment of structural variation, more recent long reads from Oxford Nanopore Technologies have already been proven invaluable for the discovery of large SVs and hold the potential to facilitate the resolution of the full SV spectrum. With many long-read sequencing studies to follow, it is crucial to assess factors affecting current SV calling pipelines for nanopore sequencing data. In this brief research report, we evaluate and compare the performances of five long-read SV callers across four long-read aligners using both real and synthetic nanopore datasets. In particular, we focus on the effects of read alignment, sequencing coverage, and variant allele depth on the detection and genotyping of SVs of different types and size ranges and provide insights into precision and recall of SV callsets generated by integrating the various long-read aligners and SV callers. The computational pipeline we propose is publicly available at https://github.com/davidebolo1993/EViNCe and can be adjusted to further evaluate future nanopore sequencing datasets.

scholarly journals Telomere-to-telomere gapless chromosomes of banana using nanopore sequencing

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Caroline Belser ◽  
Franc-Christophe Baurens ◽  
Benjamin Noel ◽  
Guillaume Martin ◽  
Corinne Cruaud ◽  
...  
Keyword(s):  
Musa Acuminata ◽  
Genetic Maps ◽  
Nanopore Sequencing ◽  
Genome Coverage ◽  
Long Reads ◽  
Oxford Nanopore ◽  
A Genome ◽  
Long Read ◽  
Genome Assemblies ◽  
First Time

AbstractLong-read technologies hold the promise to obtain more complete genome assemblies and to make them easier. Coupled with long-range technologies, they can reveal the architecture of complex regions, like centromeres or rDNA clusters. These technologies also make it possible to know the complete organization of chromosomes, which remained complicated before even when using genetic maps. However, generating a gapless and telomere-to-telomere assembly is still not trivial, and requires a combination of several technologies and the choice of suitable software. Here, we report a chromosome-scale assembly of a banana genome (Musa acuminata) generated using Oxford Nanopore long-reads. We generated a genome coverage of 177X from a single PromethION flowcell with near 17X with reads longer than 75 kbp. From the 11 chromosomes, 5 were entirely reconstructed in a single contig from telomere to telomere, revealing for the first time the content of complex regions like centromeres or clusters of paralogous genes.

scholarly journals LINKS: Scaffolding genome assemblies with kilobase-long nanopore reads

2015 ◽  
Author(s):  
Rene L Warren ◽  
Benjamin P Vandervalk ◽  
Steven JM Jones ◽  
Inanc Birol
Keyword(s):  
Genome Assembly ◽  
Error Rates ◽  
Great Promise ◽  
Genomic Information ◽  
E Coli ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Long Read ◽  
K 12 ◽  
Genome Assemblies

Owing to the complexity of the assembly problem, we do not yet have complete genome sequences. The difficulty in assembling reads into finished genomes is exacerbated by sequence repeats and the inability of short reads to capture sufficient genomic information to resolve those problematic regions. Established and emerging long read technologies show great promise in this regard, but their current associated higher error rates typically require computational base correction and/or additional bioinformatics pre-processing before they could be of value. We present LINKS, the Long Interval Nucleotide K-mer Scaffolder algorithm, a solution that makes use of the information in error-rich long reads, without the need for read alignment or base correction. We show how the contiguity of an ABySS E. coli K-12 genome assembly could be increased over five-fold by the use of beta-released Oxford Nanopore Ltd. (ONT) long reads and how LINKS leverages long-range information in S. cerevisiae W303 ONT reads to yield an assembly with less than half the errors of competing applications. Re-scaffolding the colossal white spruce assembly draft (PG29, 20 Gbp) and how LINKS scales to larger genomes is also presented. We expect LINKS to have broad utility in harnessing the potential of long reads in connecting high-quality sequences of small and large genome assembly drafts. Availability: http://www.bcgsc.ca/bioinfo/software/links

scholarly journals De novo clustering of long-read transcriptome data using a greedy, quality-value based algorithm

2018 ◽  
Author(s):  
Kristoffer Sahlin ◽  
Paul Medvedev
Keyword(s):  
Clustering Algorithm ◽  
De Novo ◽  
Substantial Improvement ◽  
Error Rates ◽  
Reconstruction Algorithms ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Long Read ◽  
Transcript Reconstruction ◽  
Oxford Nanopore Technologies

AbstractLong-read sequencing of transcripts with PacBio Iso-Seq and Oxford Nanopore Technologies has proven to be central to the study of complex isoform landscapes in many organisms. However, current de novo transcript reconstruction algorithms from long-read data are limited, leaving the potential of these technologies unfulfilled. A common bottleneck is the dearth of scalable and accurate algorithms for clustering long reads according to their gene family of origin. To address this challenge, we develop isONclust, a clustering algorithm that is greedy (in order to scale) and makes use of quality values (in order to handle variable error rates). We test isONclust on three simulated and five biological datasets, across a breadth of organisms, technologies, and read depths. Our results demonstrate that isONclust is a substantial improvement over previous approaches, both in terms of overall accuracy and/or scalability to large datasets. Our tool is available at https://github.com/ksahlin/isONclust.

scholarly journals Rapid multi-locus sequence typing direct from uncorrected long reads using Krocus

2018 ◽  
Author(s):  
Andrew J. Page ◽  
Jacqueline A. Keane
Keyword(s):  
Error Rates ◽  
Multi Locus Sequence Typing ◽  
Short Read Sequencing ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Standard Tool ◽  
Long Read ◽  
Sequence Types ◽  
Very High

AbstractGenome sequencing is rapidly being adopted in reference labs and hospitals for bacterial outbreak investigation and diagnostics where time is critical. Seven gene multi-locus sequence typing is a standard tool for broadly classifying samples into sequence types, allowing, in many cases, to rule a sample in or out of an outbreak, or allowing for general characteristics about a bacterial strain to be inferred. Long read sequencing technologies, such as from PacBio or Oxford Nanopore, can produce read data within minutes of an experiment starting, unlike short read sequencing technologies which require many hours/days. However, the error rates of raw uncorrected long read data are very high. We present Krocus which can predict a sequence type directly from uncorrected long reads, and which was designed to consume read data as it is produced, providing results in minutes. It is the only tool which can do this from uncorrected long reads. We tested Krocus on over 600 samples sequenced with using long read sequencing technologies from PacBio and Oxford Nanopore. It provides sequence types on average within 90 seconds, with a sensitivity of 94% and specificity of 97%, directly from uncorrected raw sequence reads. The software is written in Python and is available under the open source license GNU GPL version 3.

scholarly journals Telomere-to-telomere gapless chromosomes of banana using nanopore sequencing

2021 ◽  
Author(s):  
Caroline Belser ◽  
Franc-Christophe Baurens ◽  
Benjamin Noel ◽  
Guillaume Martin ◽  
Corinne Cruaud ◽  
...  
Keyword(s):  
Musa Acuminata ◽  
Genetic Maps ◽  
Nanopore Sequencing ◽  
Genome Coverage ◽  
Long Reads ◽  
Oxford Nanopore ◽  
A Genome ◽  
Long Read ◽  
Genome Assemblies ◽  
First Time

AbstractLong-read technologies hold the promise to obtain more complete genome assemblies and to make them easier. Coupled with long-range technologies, they can reveal the architecture of complex regions, like centromeres or rDNA clusters. These technologies also make it possible to know the complete organization of chromosomes, which remained complicated before even when using genetic maps. However, generating a gapless and telomere-to-telomere assembly is still not trivial, and requires a combination of several technologies and the choice of suitable software. Here, we report a chromosome-scale assembly of a banana genome (Musa acuminata) generated using Oxford Nanopore long-reads. We generated a genome coverage of 177X from a single PromethION flowcell with near 17X with reads longer than 75Kb. From the 11 chromosomes, 5 were entirely reconstructed in a single contig from telomere to telomere, revealing for the first time the content of complex regions like centromeres or clusters of paralogous genes.

scholarly journals Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation

2016 ◽  
Author(s):  
Sergey Koren ◽  
Brian P. Walenz ◽  
Konstantin Berlin ◽  
Jason R. Miller ◽  
Nicholas H. Bergman ◽  
...  
Keyword(s):  
Single Molecule ◽  
De Novo ◽  
Error Rates ◽  
Celera Assembler ◽  
Oxford Nanopore ◽  
Long Read ◽  
Reference Quality ◽  
Order Of Magnitude ◽  
Assembly Algorithms ◽  
Oxford Nanopore Technologies

AbstractLong-read single-molecule sequencing has revolutionized de novo genome assembly and enabled the automated reconstruction of reference-quality genomes. However, given the relatively high error rates of such technologies, efficient and accurate assembly of large repeats and closely related haplotypes remains challenging. We address these issues with Canu, a successor of Celera Assembler that is specifically designed for noisy single-molecule sequences. Canu introduces support for nanopore sequencing, halves depth-of-coverage requirements, and improves assembly continuity while simultaneously reducing runtime by an order of magnitude on large genomes versus Celera Assembler 8.2. These advances result from new overlapping and assembly algorithms, including an adaptive overlapping strategy based on tf-idf weighted MinHash and a sparse assembly graph construction that avoids collapsing diverged repeats and haplotypes. We demonstrate that Canu can reliably assemble complete microbial genomes and near-complete eukaryotic chromosomes using either PacBio or Oxford Nanopore technologies, and achieves a contig NG50 of greater than 21 Mbp on both human and Drosophila melanogaster PacBio datasets. For assembly structures that cannot be linearly represented, Canu provides graph-based assembly outputs in graphical fragment assembly (GFA) format for analysis or integration with complementary phasing and scaffolding techniques. The combination of such highly resolved assembly graphs with long-range scaffolding information promises the complete and automated assembly of complex genomes.

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