scholarly journals A complete bacterial genome assembled de novo using only nanopore sequencing data

2015 ◽  
Vol 12 (8) ◽  
pp. 733-735 ◽  
Author(s):  
Nicholas J Loman ◽  
Joshua Quick ◽  
Jared T Simpson
Keyword(s):  
De Novo ◽  
Bacterial Genome ◽  
Nanopore Sequencing ◽  
Sequencing Data ◽  
Complete Bacterial Genome

scholarly journals A complete bacterial genome assembled de novo using only nanopore sequencing data

2015 ◽  
Author(s):  
Nicholas James Loman ◽  
Joshua Quick ◽  
Jared T Simpson
Keyword(s):  
De Novo ◽  
Bacterial Genome ◽  
Reference Sequence ◽  
Nucleotide Identity ◽  
Sequencing Data ◽  
Celera Assembler ◽  
Level Data ◽  
Complete Bacterial Genome ◽  
Sequencing Platforms ◽  
K 12

A method for de novo assembly of data from the Oxford Nanopore MinION instrument is presented which is able to reconstruct the sequence of an entire bacterial chromosome in a single contig. Initially, overlaps between nanopore reads are detected. Reads are then subjected to one or more rounds of error correction by a multiple alignment process employing partial order graphs. After correction, reads are assembled using the Celera assembler. Finally, the assembly is polished using signal-level data from the nanopore employing a novel hidden Markov model. We show that this method is able to assemble nanopore reads from Escherichia coli K-12 MG1655 into a single contig of length 4.6Mb permitting a full reconstruction of gene order. The resulting draft assembly has 98.4% nucleotide identity compared to the finished reference genome. After polishing the assembly with our signal-level HMM, the nucleotide identity is improved to 99.4%. We show that MinION sequencing data can be used to reconstruct genomes without the need for a reference sequence or data from other sequencing platforms.

scholarly journals Evaluation of hybrid and non-hybrid methods for de novo assembly of nanopore reads

2015 ◽  
Author(s):  
Ivan Sovic ◽  
Kresimir Krizanovic ◽  
Karolj Skala ◽  
Mile Sikic
Keyword(s):  
De Novo Assembly ◽  
De Novo ◽  
Hybrid Methods ◽  
Bacterial Genome ◽  
Error Rates ◽  
Sequencing Data ◽  
E Coli ◽  
Recent Emergence ◽  
K 12

Recent emergence of nanopore sequencing technology set a challenge for the established assembly methods not optimized for the combination of read lengths and high error rates of nanopore reads. In this work we assessed how existing de novo assembly methods perform on these reads. We benchmarked three non-hybrid (in terms of both error correction and scaffolding) assembly pipelines as well as two hybrid assemblers which use third generation sequencing data to scaffold Illumina assemblies. Tests were performed on several publicly available MinION and Illumina datasets of E. coli K-12, using several sequencing coverages of nanopore data (20x, 30x, 40x and 50x). We attempted to assess the quality of assembly at each of these coverages, to estimate the requirements for closed bacterial genome assembly. Results show that hybrid methods are highly dependent on the quality of NGS data, but much less on the quality and coverage of nanopore data and perform relatively well on lower nanopore coverages. Furthermore, when coverage is above 40x, all non-hybrid methods correctly assemble the E. coli genome, even a non-hybrid method tailored for Pacific Bioscience reads. While it requires higher coverage compared to a method designed particularly for nanopore reads, its running time is significantly lower.

scholarly journals De novo species identification using 16S rRNA gene nanopore sequencing

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10029
Author(s):  
Inga Leena Angell ◽  
Morten Nilsen ◽  
Karin C. Lødrup Carlsen ◽  
Kai-Håkon Carlsen ◽  
Gunilla Hedlin ◽  
...  
Keyword(s):  
Species Identification ◽  
Vaginal Delivery ◽  
De Novo ◽  
Abundant Species ◽  
Human Infant ◽  
Rrna Gene ◽  
Nanopore Sequencing ◽  
Sequencing Data ◽  
Widespread Application ◽  
Taxonomic Assignments

Nanopore sequencing is rapidly becoming more popular for use in various microbiota-based applications. Major limitations of current approaches are that they do not enable de novo species identification and that they cannot be used to verify species assignments. This severely limits applicability of the nanopore sequencing technology in taxonomic applications. Here, we demonstrate the possibility of de novo species identification and verification using hexamer frequencies in combination with k-means clustering for nanopore sequencing data. The approach was tested on the human infant gut microbiota of 3-month-old infants. Using the hexamer k-means approach we identified two new low abundant species associated with vaginal delivery. In addition, we confirmed both the vaginal delivery association for two previously identified species and the overall high levels of bifidobacteria. Taxonomic assignments were further verified by mock community analyses. Therefore, we believe our de novo species identification approach will have widespread application in analyzing microbial communities in the future.

scholarly journals Comparative analysis of alignment tools for application on Nanopore sequencing data

2021 ◽  
Vol 7 (2) ◽  
pp. 831-834
Author(s):  
Chiara Becht ◽  
Jonas Schmidt ◽  
Frithjof Blessing ◽  
Folker Wenzel
Keyword(s):  
Error Rate ◽  
De Novo ◽  
Performance Criteria ◽  
Computational Time ◽  
Nanopore Sequencing ◽  
Sequencing Data ◽  
Accurate Analysis ◽  
Match Rate ◽  
Long Read ◽  
And Performance

Abstract INTRODUCTION: Long-read sequencing techniques such as Oxford Nanopore sequencing, are representing a promising novel approach in molecular-biological methodology, enabling potential facilitation in mapping and de novo assembly. In comparison to conventional sequencing methods, novel alignment tools are mandated to compensate differing data structures (especially high error rate) to achieve acceptably accurate analysis results. METHODS: In this study, benchmarking for long read aligners BLASR, GraphMap, LAST, minimap2, NGMLR and the short-read aligner BWA MEM on three experimental datasets was conducted. Obtained alignment results were compared for various quality and performance criteria, such as match rate, mismatch rate, error rate, working memory usage and computational time. RESULTS: The comparison yielded differences in alignment quality and performance of tools under test. Tool LAST showed the largest differences among all tools. Minimap2 achieved constant quality with good performance. BLASR, GraphMap, BWA MEM and NGMLR showed slight differences only. CONCLUSION: Differences among the tools could be reasoned with dataset characteristics and algorithm approaches of individual tools. All tools except BLASR seem applicable for Nanopore sequencing data. Therefore, selection of the tool should be done under consideration of the experimental design and the further downstream analysis

scholarly journals Reconstructing the Gigabase Plant Genome of Solanum pennellii using Nanopore Sequencing

2017 ◽  
Author(s):  
Maximilian H.-W. Schmidt ◽  
Alxander Vogel ◽  
Alisandra K. Denton ◽  
Benjamin Istace ◽  
Alexandra Wormit ◽  
...  
Keyword(s):  
Error Rate ◽  
De Novo ◽  
Sequence Data ◽  
Fragment Size ◽  
Plant Genome ◽  
Nanopore Sequencing ◽  
Sequencing Data ◽  
Sequencing Technology ◽  
Solanum Pennellii ◽  
Wild Tomato Species

Recent updates in sequencing technology have made it possible to obtain Gigabases of sequence data from one single flowcell. Prior to this update, the nanopore sequencing technology was mainly used to analyze and assemble microbial samples1-3. Here, we describe the generation of a comprehensive nanopore sequencing dataset with a median fragment size of 11,979 bp for the wild tomato species Solanum pennellii featuring an estimated genome size of ca 1.0 to 1.1 Gbases. We describe its genome assembly to a contig N50 of 2.5 MB using a pipeline comprising a Canu4 pre-processing and a subsequent assembly using SMARTdenovo. We show that the obtained nanopore based de novo genome reconstruction is structurally highly similar to that of the reference S. pennellii LA7165 genome but has a high error rate caused mostly by deletions in homopolymers. After polishing the assembly with Illumina short read data we obtained an error rate of <0.02 % when assessed versus the same Illumina data. More importantly however we obtained a gene completeness of 96.53% which even slightly surpasses that of the reference S. pennellii genome5. Taken together our data indicate such long read sequencing data can be used to affordably sequence and assemble Gbase sized diploid plant genomes.Raw data is available at http://www.plabipd.de/portal/solanum-pennellii and has been deposited as PRJEB19787.

scholarly journals On the (Im)possibility to Reconstruct Plasmids from Whole Genome Short-Read Sequencing Data

2016 ◽  
Author(s):  
Sergio Arredondo-Alonso ◽  
Willem van Schaik ◽  
Rob J. Willems ◽  
Anita C. Schürch
Keyword(s):  
Complete Genome ◽  
De Novo ◽  
Bacterial Genome ◽  
Composition Analysis ◽  
Bacterial Survival ◽  
Sequencing Data ◽  
Genome Sequences ◽  
High Throughput Analysis ◽  
Short Read ◽  
Short Read Sequencing

AbstractPlasmids are autonomous extra-chromosomal elements in bacterial cells that can carry genes that are important for bacterial survival. To benchmark algorithms for automated plasmid sequence reconstruction from short read sequencing data, we selected 42 publicly available complete bacterial genome sequences which were assembled by a combination of long- and short-read data. The selected bacterial genome sequence projects span 12 genera, containing 148 plasmids. We predicted plasmids from short-read data with four different programs (PlasmidSPAdes, Recycler, cBar and PlasmidFinder) and compared the outcome to the reference sequences.PlasmidSPAdes reconstructs plasmids based on coverage differences in the assembly graph. It reconstructed most of the reference plasmids (recall = 0.82) but approximately a quarter of the predicted plasmid contigs were false positives (precision = 0.76). PlasmidSPAdes merged 83 % of the predictions from genomes with multiple plasmids in a single bin. Recycler searches the assembly graph for sub-graphs corresponding to circular sequences and correctly predicted small plasmids but failed with long plasmids (recall = 0.12, precision = 0.30). cBar, which applies pentamer frequency composition analysis to detect plasmid-derived contigs, showed an overall recall and precision of 0.78 and 0.64. However, cBar only categorizes contigs as plasmid-derived and does not bin the different plasmids correctly within a bacterial isolate. PlasmidFinder, which searches for matches in a replicon database, had the highest precision (1.0) but was restricted by the contents of its database and the contig length obtained from de novo assembly (recall = 0.36).Surprisingly, PlasmidSPAdes and Recycler detected single isolated components corresponding to putative novel small plasmids (<10 kbp) which were also predicted as plasmids by cBar.This study shows that it is possible to automatically predict plasmid sequences, but only for small plasmids. The reconstruction of large plasmids (>50 kbp) containing repeated sequences remains challenging and limits the high-throughput analysis of WGS data.Author SummaryShort read sequencing of the DNA of bacteria is often used to understand characteristics such as antibiotic resistance. However the assembly of short read sequencing data with the goal of reconstructing a complete genome is often fragmented and leaves gaps. Therefore independently replicating DNA fragments called plasmids cannot easily be identified from an assembly. Lately a number of programs have been developed to enable the automated prediction of the sequences of plasmids. Here we tested these programs by comparing their outcomes with complete genome sequences. None of the tested programs were able to fully and unambiguously predict distinct plasmid sequences. All programs performed best with the prediction of plasmids smaller than 50 kbp. Larger plasmids were only correctly predicted if they were present as a single contig in the assembly. While predictions by PlasmidSPAdes and cBar contained most of the plasmids, they were merged with or indistinguishable from other plasmids and sometimes chromosome sequences. PlasmidFinder missed most plasmids but all its predictions were correct. Without manual steps or long-read sequencing information, plasmid reconstruction from short read sequencing data remains challenging.

scholarly journals Comparison of De Novo Assembly Strategies for Bacterial Genomes

2021 ◽  
Vol 22 (14) ◽  
pp. 7668
Author(s):  
Pengfei Zhang ◽  
Dike Jiang ◽  
Yin Wang ◽  
Xueping Yao ◽  
Yan Luo ◽  
...  
Keyword(s):  
De Novo ◽  
Bacterial Genome ◽  
Sequencing Data ◽  
Bacterial Genomes ◽  
Accurate Analysis ◽  
Short Read ◽  
Sequencing Errors ◽  
Assembly Accuracy ◽  
Protein Prediction ◽  
Long Read

(1) Background: Short-read sequencing allows for the rapid and accurate analysis of the whole bacterial genome but does not usually enable complete genome assembly. Long-read sequencing greatly assists with the resolution of complex bacterial genomes, particularly when combined with short-read Illumina data. However, it is not clear how different assembly strategies affect genomic accuracy, completeness, and protein prediction. (2) Methods: we compare different assembly strategies for Haemophilus parasuis, which causes Glässer’s disease, characterized by fibrinous polyserositis and arthritis, in swine by using Illumina sequencing and long reads from the sequencing platforms of either Oxford Nanopore Technologies (ONT) or SMRT Pacific Biosciences (PacBio). (3) Results: Assembly with either PacBio or ONT reads, followed by polishing with Illumina reads, facilitated high-quality genome reconstruction and was superior to the long-read-only assembly and hybrid-assembly strategies when evaluated in terms of accuracy and completeness. An equally excellent method was correction with Homopolish after the ONT-only assembly, which had the advantage of avoiding hybrid sequencing with Illumina. Furthermore, by aligning transcripts to assembled genomes and their predicted CDSs, the sequencing errors of the ONT assembly were mainly indels that were generated when homopolymer regions were sequenced, thus critically affecting protein prediction. Polishing can fill indels and correct mistakes. (4) Conclusions: The assembly of bacterial genomes can be directly achieved by using long-read sequencing techniques. To maximize assembly accuracy, it is essential to polish the assembly with homologous sequences of related genomes or sequencing data from short-read technology.

scholarly journals Comparison of long-read sequencing technologies in interrogating bacteria and fly genomes

2021 ◽  
Author(s):  
Eric S Tvedte ◽  
Mark Gasser ◽  
Benjamin C Sparklin ◽  
Jane Michalski ◽  
Carl E Hjelmen ◽  
...  
Keyword(s):  
Bacterial Genome ◽  
Hybrid Approach ◽  
Cost Effective ◽  
Fruit Fly ◽  
Drosophila Ananassae ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
E Coli ◽  
Hybrid Approaches ◽  
Long Read

Abstract The newest generation of DNA sequencing technology is highlighted by the ability to generate sequence reads hundreds of kilobases in length. Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) have pioneered competitive long read platforms, with more recent work focused on improving sequencing throughput and per-base accuracy. We used whole-genome sequencing data produced by three PacBio protocols (Sequel II CLR, Sequel II HiFi, RS II) and two ONT protocols (Rapid Sequencing and Ligation Sequencing) to compare assemblies of the bacteria Escherichia coli and the fruit fly Drosophila ananassae. In both organisms tested, Sequel II assemblies had the highest consensus accuracy, even after accounting for differences in sequencing throughput. ONT and PacBio CLR had the longest reads sequenced compared to PacBio RS II and HiFi, and genome contiguity was highest when assembling these datasets. ONT Rapid Sequencing libraries had the fewest chimeric reads in addition to superior quantification of E. coli plasmids versus ligation-based libraries. The quality of assemblies can be enhanced by adopting hybrid approaches using Illumina libraries for bacterial genome assembly or polishing eukaryotic genome assemblies, and an ONT-Illumina hybrid approach would be more cost-effective for many users. Genome-wide DNA methylation could be detected using both technologies, however ONT libraries enabled the identification of a broader range of known E. coli methyltransferase recognition motifs in addition to undocumented D. ananassae motifs. The ideal choice of long read technology may depend on several factors including the question or hypothesis under examination. No single technology outperformed others in all metrics examined.

scholarly journals METAMVGL: a multi-view graph-based metagenomic contig binning algorithm by integrating assembly and paired-end graphs

2021 ◽  
Vol 22 (S10) ◽  
Author(s):  
Zhenmiao Zhang ◽  
Lu Zhang
Keyword(s):  
De Novo ◽  
Label Propagation ◽  
Next Generation Sequencing Data ◽  
Metagenomic Sequencing ◽  
Sequencing Data ◽  
Fecal Samples ◽  
Microbial Genomes ◽  
Metagenome Assembly ◽  
High Chance ◽  
Mock Communities

Abstract Background Due to the complexity of microbial communities, de novo assembly on next generation sequencing data is commonly unable to produce complete microbial genomes. Metagenome assembly binning becomes an essential step that could group the fragmented contigs into clusters to represent microbial genomes based on contigs’ nucleotide compositions and read depths. These features work well on the long contigs, but are not stable for the short ones. Contigs can be linked by sequence overlap (assembly graph) or by the paired-end reads aligned to them (PE graph), where the linked contigs have high chance to be derived from the same clusters. Results We developed METAMVGL, a multi-view graph-based metagenomic contig binning algorithm by integrating both assembly and PE graphs. It could strikingly rescue the short contigs and correct the binning errors from dead ends. METAMVGL learns the two graphs’ weights automatically and predicts the contig labels in a uniform multi-view label propagation framework. In experiments, we observed METAMVGL made use of significantly more high-confidence edges from the combined graph and linked dead ends to the main graph. It also outperformed many state-of-the-art contig binning algorithms, including MaxBin2, MetaBAT2, MyCC, CONCOCT, SolidBin and GraphBin on the metagenomic sequencing data from simulation, two mock communities and Sharon infant fecal samples. Conclusions Our findings demonstrate METAMVGL outstandingly improves the short contig binning and outperforms the other existing contig binning tools on the metagenomic sequencing data from simulation, mock communities and infant fecal samples.

scholarly journals SLR-superscaffolder: a de novo scaffolding tool for synthetic long reads using a top-to-bottom scheme

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Lidong Guo ◽  
Mengyang Xu ◽  
Wenchao Wang ◽  
Shengqiang Gu ◽  
Xia Zhao ◽  
...  
Keyword(s):  
High Efficiency ◽  
De Novo ◽  
Next Generation Sequencing Data ◽  
Sequencing Data ◽  
Draft Assembly ◽  
Screening Algorithm ◽  
Long Reads ◽  
Hybrid Genome ◽  
Genomics Research ◽  
Negative Effect

Abstract Background Synthetic long reads (SLR) with long-range co-barcoding information are now widely applied in genomics research. Although several tools have been developed for each specific SLR technique, a robust standalone scaffolder with high efficiency is warranted for hybrid genome assembly. Results In this work, we developed a standalone scaffolding tool, SLR-superscaffolder, to link together contigs in draft assemblies using co-barcoding and paired-end read information. Our top-to-bottom scheme first builds a global scaffold graph based on Jaccard Similarity to determine the order and orientation of contigs, and then locally improves the scaffolds with the aid of paired-end information. We also exploited a screening algorithm to reduce the negative effect of misassembled contigs in the input assembly. We applied SLR-superscaffolder to a human single tube long fragment read sequencing dataset and increased the scaffold NG50 of its corresponding draft assembly 1349 fold. Moreover, benchmarking on different input contigs showed that this approach overall outperformed existing SLR scaffolders, providing longer contiguity and fewer misassemblies, especially for short contigs assembled by next-generation sequencing data. The open-source code of SLR-superscaffolder is available at https://github.com/BGI-Qingdao/SLR-superscaffolder. Conclusions SLR-superscaffolder can dramatically improve the contiguity of a draft assembly by integrating a hybrid assembly strategy.

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