scholarly journals Comparison of long-read sequencing technologies in the hybrid assembly of complex bacterial genomes

2019 ◽  
Author(s):  
Nicola De Maio ◽  
Liam P. Shaw ◽  
Alasdair Hubbard ◽  
Sophie George ◽  
Nick Sanderson ◽  
...  
Keyword(s):  
Bacterial Genome ◽  
Hybrid Assembly ◽  
Bacterial Genomes ◽  
Short Read ◽  
Short Reads ◽  
Genome Reconstruction ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Long Read ◽  
Sequencing Platforms

ABSTRACTIllumina sequencing allows rapid, cheap and accurate whole genome bacterial analyses, but short reads (<300 bp) do not usually enable complete genome assembly. Long read sequencing greatly assists with resolving complex bacterial genomes, particularly when combined with short-read Illumina data (hybrid assembly). However, it is not clear how different long-read sequencing methods impact on assembly accuracy. Relative automation of the assembly process is also crucial to facilitating high-throughput complete bacterial genome reconstruction, avoiding multiple bespoke filtering and data manipulation steps. In this study, we compared hybrid assemblies for 20 bacterial isolates, including two reference strains, using Illumina sequencing and long reads from either Oxford Nanopore Technologies (ONT) or from SMRT Pacific Biosciences (PacBio) sequencing platforms. We chose isolates from the Enterobacteriaceae family, as these frequently have highly plastic, repetitive genetic structures and complete genome reconstruction for these species is relevant for a precise understanding of the epidemiology of antimicrobial resistance. We de novo assembled genomes using the hybrid assembler Unicycler and compared different read processing strategies. Both strategies facilitate high-quality genome reconstruction. Combining ONT and Illumina reads fully resolved most genomes without additional manual steps, and at a lower consumables cost per isolate in our setting. Automated hybrid assembly is a powerful tool for complete and accurate bacterial genome assembly.IMPACT STATEMENTIllumina short-read sequencing is frequently used for tasks in bacterial genomics, such as assessing which species are present within samples, checking if specific genes of interest are present within individual isolates, and reconstructing the evolutionary relationships between strains. However, while short-read sequencing can reveal significant detail about the genomic content of bacterial isolates, it is often insufficient for assessing genomic structure: how different genes are arranged within genomes, and particularly which genes are on plasmids – potentially highly mobile components of the genome frequently carrying antimicrobial resistance elements. This is because Illumina short reads are typically too short to span repetitive structures in the genome, making it impossible to accurately reconstruct these repetitive regions. One solution is to complement Illumina short reads with long reads generated with SMRT Pacific Biosciences (PacBio) or Oxford Nanopore Technologies (ONT) sequencing platforms. Using this approach, called ‘hybrid assembly’, we show that we can automatically fully reconstruct complex bacterial genomes of Enterobacteriaceae isolates in the majority of cases (best-performing method: 17/20 isolates). In particular, by comparing different methods we find that using the assembler Unicycler with Illumina and ONT reads represents a low-cost, high-quality approach for reconstructing bacterial genomes using publicly available software.DATA SUMMARYRaw sequencing data and assemblies have been deposited in NCBI under BioProject Accession PRJNA422511 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA422511). We confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.

scholarly journals Long read metagenomics, the next step?

2020 ◽  
Author(s):  
Jose M. Haro-Moreno ◽  
Mario López-Pérez ◽  
Francisco Rodríguez-Valera
Keyword(s):  
Error Rate ◽  
Population Genomics ◽  
Short Read ◽  
Short Reads ◽  
Third Generation Sequencing ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Flexible Genome ◽  
Long Read ◽  
Generation Sequencing

ABSTRACTBackgroundThird-generation sequencing has penetrated little in metagenomics due to the high error rate and dependence for assembly on short-read designed bioinformatics. However, 2nd generation sequencing metagenomics (mostly Illumina) suffers from limitations, particularly in allowing assembly of microbes with high microdiversity or retrieving the flexible (adaptive) compartment of prokaryotic genomes.ResultsHere we have used different 3rd generation techniques to study the metagenome of a well-known marine sample from the mixed epipelagic water column of the winter Mediterranean. We have compared Oxford Nanopore and PacBio last generation technologies with the classical approach using Illumina short reads followed by assembly. PacBio Sequel II CCS appears particularly suitable for cellular metagenomics due to its low error rate. Long reads allow efficient direct retrieval of complete genes (473M/Tb) and operons before assembly, facilitating annotation and compensates the limitations of short reads or short-read assemblies. MetaSPAdes was the most appropriate assembly program when used in combination with short reads. The assemblies of the long reads allow also the reconstruction of much more complete metagenome-assembled genomes, even from microbes with high microdiversity. The flexible genome of reconstructed MAGs is much more complete and allows rescuing more adaptive genes.ConclusionsFor most applications of metagenomics, from community structure analysis to ecosystem functioning, long-reads should be applied whenever possible. Particularly for in-silico screening of biotechnologically useful genes, or population genomics, long-read metagenomics appears presently as a very fruitful approach and can be used from raw reads, before a computing-demanding (and potentially artefactual) assembly step.

scholarly journals Trycycler: consensus long-read assemblies for bacterial genomes

2021 ◽  
Author(s):  
Ryan R Wick ◽  
Louise M Judd ◽  
Louise T Cerdeira ◽  
Jane Hawkey ◽  
Guillaume Meric ◽  
...  
Keyword(s):  
Bacterial Genome ◽  
Bacterial Genomes ◽  
Manual Intervention ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Multiple Input ◽  
Long Read ◽  
Complete Bacterial Genome ◽  
Genome Assemblies ◽  
Reference Genomes

Assembly of bacterial genomes from long-read data (generated by Oxford Nanopore or Pacific Biosciences platforms) can often be complete: a single contig for each chromosome or plasmid in the genome. However, even complete bacterial genome assemblies constructed solely from long reads still contain a variety of errors, and different assemblies of the same genome often contain different errors. Here, we present Trycycler, a tool which produces a consensus assembly from multiple input assemblies of the same genome. Benchmarking using both simulated and real sequencing reads showed that Trycycler consensus assemblies contained fewer errors than any of those constructed with a single long-read assembler. Post-assembly polishing with Medaka and Pilon further reduced errors and yielded the most accurate genome assemblies in our study. As Trycycler can require human judgement and manual intervention, its output is not deterministic, and different users can produce different Trycycler assemblies from the same input data. However, we demonstrated that multiple users with minimal training converge on similar assemblies that are consistently more accurate than those produced by automated assembly tools. We therefore recommend Trycycler+Medaka+Pilon as an ideal approach for generating high-quality bacterial reference genomes.

scholarly journals Assembly methods for nanopore-based metagenomic sequencing: a comparative study

2019 ◽  
Author(s):  
Adriel Latorre-Pérez ◽  
Pascual Villalba-Bermell ◽  
Javier Pascual ◽  
Manuel Porcar ◽  
Cristina Vilanova
Keyword(s):  
Bacterial Genome ◽  
Gene Clusters ◽  
Systematic Evaluation ◽  
Metagenomic Sequencing ◽  
Sequencing Data ◽  
Short Reads ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Sequencing Platforms

ABSTRACTBackgroundMetagenomic sequencing has lead to the recovery of previously unexplored microbial genomes. In this sense, short-reads sequencing platforms often result in highly fragmented metagenomes, thus complicating downstream analyses. Third generation sequencing technologies, such as MinION, could lead to more contiguous assemblies due to their ability to generate long reads. Nevertheless, there is a lack of studies evaluating the suitability of the available assembly tools for this new type of data.FindingsWe benchmarked the ability of different short-reads and long-reads tools to assembly two different commercially available mock communities, and observed remarkable differences in the resulting assemblies depending on the software of choice. Short-reads metagenomic assemblers proved unsuitable for MinION data. Among the long-reads assemblers tested, Flye and Canu were the only ones performing well in all the datasets. These tools were able to retrieve complete individual genomes directly from the metagenome, and assembled a bacterial genome in only two contigs in the best scenario. Despite the intrinsic high error of long-reads technologies, Canu and Flye lead to high accurate assemblies (~99.4-99.8 % of accuracy). However, errors still had an impact on the prediction of biosynthetic gene clusters.ConclusionsMinION metagenomic sequencing data proved sufficient for assembling low-complex microbial communities, leading to the recovery of highly complete and contiguous individual genomes. This work is the first systematic evaluation of the performance of different assembly tools on MinION data, and may help other researchers willing to use this technology to choose the most appropriate software depending on their goals. Future work is still needed in order to assess the performance of Oxford Nanopore MinION data on more complex microbiomes.

scholarly journals Evaluating the accuracy of Listeria monocytogenes assemblies from quasimetagenomic samples using long and short reads

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Seth Commichaux ◽  
Kiran Javkar ◽  
Padmini Ramachandran ◽  
Niranjan Nagarajan ◽  
Denis Bertrand ◽  
...  
Keyword(s):  
Public Health ◽  
Public Health Response ◽  
High Quality ◽  
Short Read ◽  
Short Reads ◽  
The Core ◽  
Long Reads ◽  
Health Response ◽  
Long Read ◽  
Core Genes

Abstract Background Whole genome sequencing of cultured pathogens is the state of the art public health response for the bioinformatic source tracking of illness outbreaks. Quasimetagenomics can substantially reduce the amount of culturing needed before a high quality genome can be recovered. Highly accurate short read data is analyzed for single nucleotide polymorphisms and multi-locus sequence types to differentiate strains but cannot span many genomic repeats, resulting in highly fragmented assemblies. Long reads can span repeats, resulting in much more contiguous assemblies, but have lower accuracy than short reads. Results We evaluated the accuracy of Listeria monocytogenes assemblies from enrichments (quasimetagenomes) of naturally-contaminated ice cream using long read (Oxford Nanopore) and short read (Illumina) sequencing data. Accuracy of ten assembly approaches, over a range of sequencing depths, was evaluated by comparing sequence similarity of genes in assemblies to a complete reference genome. Long read assemblies reconstructed a circularized genome as well as a 71 kbp plasmid after 24 h of enrichment; however, high error rates prevented high fidelity gene assembly, even at 150X depth of coverage. Short read assemblies accurately reconstructed the core genes after 28 h of enrichment but produced highly fragmented genomes. Hybrid approaches demonstrated promising results but had biases based upon the initial assembly strategy. Short read assemblies scaffolded with long reads accurately assembled the core genes after just 24 h of enrichment, but were highly fragmented. Long read assemblies polished with short reads reconstructed a circularized genome and plasmid and assembled all the genes after 24 h enrichment but with less fidelity for the core genes than the short read assemblies. Conclusion The integration of long and short read sequencing of quasimetagenomes expedited the reconstruction of a high quality pathogen genome compared to either platform alone. A new and more complete level of information about genome structure, gene order and mobile elements can be added to the public health response by incorporating long read analyses with the standard short read WGS outbreak response.

scholarly journals Complete Genome Sequences of 12 Quinolone-Resistant Escherichia coli Strains Containing qnrS1 Based on Hybrid Assemblies

2021 ◽  
Vol 10 (4) ◽  
Author(s):  
Håkon Kaspersen ◽  
Thomas H. A. Haverkamp ◽  
Hanna Karin Ilag ◽  
Øivind Øines ◽  
Camilla Sekse ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Complete Genome ◽  
Flow Cell ◽  
Hybrid Assembly ◽  
Genome Sequences ◽  
Content Type ◽  
Short Reads ◽  
Long Reads ◽  
Long Read ◽  
Hybrid Assemblies

ABSTRACT In total, 12 quinolone-resistant Escherichia coli (QREC) strains containing qnrS1 were submitted to long-read sequencing using a FLO-MIN106 flow cell on a MinION device. The long reads were assembled with short reads (Illumina) and analyzed using the MOB-suite pipeline. Six of these QREC genome sequences were closed after hybrid assembly.

scholarly journals Assembling reads improves taxonomic classification of species

2020 ◽  
Author(s):  
Quang Tran ◽  
Vinhthuy Phan
Keyword(s):  
Classification Performance ◽  
Performance Characteristics ◽  
Metagenomic Data ◽  
Species Classification ◽  
Short Read ◽  
Short Reads ◽  
Sequencing Errors ◽  
Trade Offs ◽  
Long Reads ◽  
Long Read

Abstract Background: Most current metagenomic classifiers and profilers employ short reads to classify, bin and profile microbial genomes that are present in metagenomic samples. Many of these methods adopt techniques that aim to identify unique genomic regions of genomes so as to differentiate them. Because of this, short-read lengths might be suboptimal. Longer read lengths might improve the performance of classification and profiling. However, longer reads produced by current technology tend to have a higher rate of sequencing errors, compared to short reads. It is not clear if the trade-off between longer length versus higher sequencing errors will increase or decrease classification and profiling performance.Results: We compared performance of popular metagenomic classifiers on short reads and longer reads, which are assembled from the same short reads. When using a number of popular assemblers to assemble long reads from the short reads, we discovered that most classifiers made fewer predictions with longer reads and that they achieved higher classification performance on synthetic metagenomic data. Specifically, across most classifiers, we observed a significant increase in precision, while recall remained the same, resulting in higher overall classification performance. On real metagenomic data, we observed a similar trend that classifiers made fewer predictions. This suggested that they might have the same performance characteristics of having higher precision while maintaining the same recall with longer reads.Conclusions: This finding has two main implications. First, it suggests that classifying species in metagenomic environments can be achieved with higher overall performance simply by assembling short reads. This suggested that they might have the same performance characteristics of having higher precision while maintaining the same recall as shorter reads. Second, this finding suggests that it might be a good idea to consider utilizing long-read technologies in species classification for metagenomic applications. Current long-read technologies tend to have higher sequencing errors and are more expensive compared to short-read technologies. The trade-offs between the pros and cons should be investigated.

scholarly journals Fast-SG: An alignment-free algorithm for hybrid assembly

2017 ◽  
Author(s):  
Alex Di Genova ◽  
Gonzalo A. Ruz ◽  
Marie-France Sagot ◽  
Alejandro Maass
Keyword(s):  
De Novo ◽  
Reference Level ◽  
Hybrid Assembly ◽  
Short Read ◽  
Sequencing Technologies ◽  
Alignment Free ◽  
Long Reads ◽  
Long Read ◽  
Definition Of ◽  
Large Genomes

ABSTRACTLong read sequencing technologies are the ultimate solution for genome repeats, allowing near reference level reconstructions of large genomes. However, long read de novo assembly pipelines are computationally intense and require a considerable amount of coverage, thereby hindering their broad application to the assembly of large genomes. Alternatively, hybrid assembly methods which combine short and long read sequencing technologies can reduce the time and cost required to produce de novo assemblies of large genomes. In this paper, we propose a new method, called FAST-SG, which uses a new ultra-fast alignment-free algorithm specifically designed for constructing a scaffolding graph using light-weight data structures. FAST-SG can construct the graph from either short or long reads. This allows the reuse of efficient algorithms designed for short read data and permits the definition of novel modular hybrid assembly pipelines. Using comprehensive standard datasets and benchmarks, we show how FAST-SG outperforms the state-of-the-art short read aligners when building the scaffolding graph, and can be used to extract linking information from either raw or error-corrected long reads. We also show how a hybrid assembly approach using FAST-SG with shallow long read coverage (5X) and moderate computational resources can produce long-range and accurate reconstructions of the genomes of Arabidopsis thaliana (Ler-0) and human (NA12878).

scholarly journals A hybrid and scalable error correction algorithm for indel and substitution errors of long reads

BMC Genomics ◽  
2019 ◽  
Vol 20 (S11) ◽  
Author(s):  
Arghya Kusum Das ◽  
Sayan Goswami ◽  
Kisung Lee ◽  
Seung-Jong Park
Keyword(s):  
Error Correction ◽  
Error Rates ◽  
De Bruijn Graph ◽  
Correction Algorithm ◽  
Short Read ◽  
Short Reads ◽  
Long Reads ◽  
Long Read ◽  
De Bruijn ◽  
Error Correction Algorithm

Abstract Background Long-read sequencing has shown the promises to overcome the short length limitations of second-generation sequencing by providing more complete assembly. However, the computation of the long sequencing reads is challenged by their higher error rates (e.g., 13% vs. 1%) and higher cost ($0.3 vs. $0.03 per Mbp) compared to the short reads. Methods In this paper, we present a new hybrid error correction tool, called ParLECH (Parallel Long-read Error Correction using Hybrid methodology). The error correction algorithm of ParLECH is distributed in nature and efficiently utilizes the k-mer coverage information of high throughput Illumina short-read sequences to rectify the PacBio long-read sequences.ParLECH first constructs a de Bruijn graph from the short reads, and then replaces the indel error regions of the long reads with their corresponding widest path (or maximum min-coverage path) in the short read-based de Bruijn graph. ParLECH then utilizes the k-mer coverage information of the short reads to divide each long read into a sequence of low and high coverage regions, followed by a majority voting to rectify each substituted error base. Results ParLECH outperforms latest state-of-the-art hybrid error correction methods on real PacBio datasets. Our experimental evaluation results demonstrate that ParLECH can correct large-scale real-world datasets in an accurate and scalable manner. ParLECH can correct the indel errors of human genome PacBio long reads (312 GB) with Illumina short reads (452 GB) in less than 29 h using 128 compute nodes. ParLECH can align more than 92% bases of an E. coli PacBio dataset with the reference genome, proving its accuracy. Conclusion ParLECH can scale to over terabytes of sequencing data using hundreds of computing nodes. The proposed hybrid error correction methodology is novel and rectifies both indel and substitution errors present in the original long reads or newly introduced by the short reads.

scholarly journals Improved Transcriptome Assembly Using a Hybrid of Long and Short Reads with StringTie

2021 ◽  
Author(s):  
Alaina Shumate ◽  
Brandon Wong ◽  
Geo Pertea ◽  
Mihaela Pertea
Keyword(s):  
Rna Sequencing ◽  
Open Source Software ◽  
Transcriptome Assembly ◽  
Simulated Data ◽  
Real Data ◽  
Short Read ◽  
Short Reads ◽  
Long Reads ◽  
Long Read ◽  
Improved Accuracy

Short-read RNA sequencing and long-read RNA sequencing each have their strengths and weaknesses for transcriptome assembly. While short reads are highly accurate, they are unable to span multiple exons. Long-read technology can capture full-length transcripts, but its high error rate often leads to mis-identified splice sites, and its low throughput makes quantification difficult. Here we present a new release of StringTie that performs hybrid-read assembly. By taking advantage of the strengths of both long and short reads, hybrid-read assembly with StringTie is more accurate than long-read only or short-read only assembly, and on some datasets it can more than double the number of correctly assembled transcripts, while obtaining substantially higher precision than the long-read data assembly alone. Here we demonstrate the improved accuracy on simulated data and real data from Arabidopsis thaliana, Mus musculus,and human. We also show that hybrid-read assembly is more accurate than correcting long reads prior to assembly while also being substantially faster. StringTie is freely available as open source software at https://github.com/gpertea/stringtie.

scholarly journals CaBagE: A Cas9-based Background Elimination strategy for targeted, long-read DNA sequencing

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0241253
Author(s):  
Amelia D. Wallace ◽  
Thomas A. Sasani ◽  
Jordan Swanier ◽  
Brooke L. Gates ◽  
Jeff Greenland ◽  
...  
Keyword(s):  
Dna Sequencing ◽  
Tandem Repeats ◽  
Short Read ◽  
Background Elimination ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Long Read ◽  
Repeat Expansions ◽  
Sequencing Platforms ◽  
Als Patients

A substantial fraction of the human genome is difficult to interrogate with short-read DNA sequencing technologies due to paralogy, complex haplotype structures, or tandem repeats. Long-read sequencing technologies, such as Oxford Nanopore’s MinION, enable direct measurement of complex loci without introducing many of the biases inherent to short-read methods, though they suffer from relatively lower throughput. This limitation has motivated recent efforts to develop amplification-free strategies to target and enrich loci of interest for subsequent sequencing with long reads. Here, we present CaBagE, a method for target enrichment that is efficient and useful for sequencing large, structurally complex targets. The CaBagE method leverages the stable binding of Cas9 to its DNA target to protect desired fragments from digestion with exonuclease. Enriched DNA fragments are then sequenced with Oxford Nanopore’s MinION long-read sequencing technology. Enrichment with CaBagE resulted in a median of 116X coverage (range 39–416) of target loci when tested on five genomic targets ranging from 4-20kb in length using healthy donor DNA. Four cancer gene targets were enriched in a single reaction and multiplexed on a single MinION flow cell. We further demonstrate the utility of CaBagE in two ALS patients with C9orf72 short tandem repeat expansions to produce genotype estimates commensurate with genotypes derived from repeat-primed PCR for each individual. With CaBagE there is a physical enrichment of on-target DNA in a given sample prior to sequencing. This feature allows adaptability across sequencing platforms and potential use as an enrichment strategy for applications beyond sequencing. CaBagE is a rapid enrichment method that can illuminate regions of the ‘hidden genome’ underlying human disease.

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