scholarly journals Polypolish: short-read polishing of long-read bacterial genome assemblies

2021 ◽  
Author(s):  
Ryan R Wick ◽  
Kathryn E Holt
Keyword(s):  
Bacterial Genome ◽  
Short Read ◽  
Read Alignment ◽  
Short Reads ◽  
Repeat Sequences ◽  
Short Read Alignment ◽  
Long Read ◽  
Genome Assemblies ◽  
Residual Errors

Long-read-only bacterial genome assemblies usually contain residual errors, most commonly homopolymer-length errors. Short-read polishing tools can use short reads to fix these errors, but most rely on short-read alignment which is unreliable in repeat regions. Errors in such regions are therefore challenging to fix and often remain after short-read polishing. Here we introduce Polypolish, a new short-read polisher which uses all-per-read alignments to repair errors in repeat sequences that other polishers cannot. In benchmarking tests using both simulated and real reads, we find that Polypolish performs well, and the best results are achieved by using Polypolish in combination with other short-read polishers.

scholarly journals DNA short read alignment on apache spark

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maryam AlJame ◽  
Imtiaz Ahmad
Keyword(s):  
Cluster Computing ◽  
Empirical Evaluation ◽  
Biological Data ◽  
Apache Spark ◽  
Short Read ◽  
Read Alignment ◽  
Short Reads ◽  
Short Read Alignment ◽  
Alignment Problem ◽  
Amazon Web Services

The evolution of technologies has unleashed a wealth of challenges by generating massive amount of data. Recently, biological data has increased exponentially, which has introduced several computational challenges. DNA short read alignment is an important problem in bioinformatics. The exponential growth in the number of short reads has increased the need for an ideal platform to accelerate the alignment process. Apache Spark is a cluster-computing framework that involves data parallelism and fault tolerance. In this article, we proposed a Spark-based algorithm to accelerate DNA short reads alignment problem, and it is called Spark-DNAligning. Spark-DNAligning exploits Apache Spark ’s performance optimizations such as broadcast variable, join after partitioning, caching, and in-memory computations. Spark-DNAligning is evaluated in term of performance by comparing it with SparkBWA tool and a MapReduce based algorithm called CloudBurst. All the experiments are conducted on Amazon Web Services (AWS). Results demonstrate that Spark-DNAligning outperforms both tools by providing a speedup in the range of 101–702 in aligning gigabytes of short reads to the human genome. Empirical evaluation reveals that Apache Spark offers promising solutions to DNA short reads alignment problem.

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 Bacterial genome reduction as a result of short read sequence assembly

2016 ◽  
Author(s):  
Charles H.D. Williamson ◽  
Andrew Sanchez ◽  
Adam Vazquez ◽  
Joshua Gutman ◽  
Jason W. Sahl
Keyword(s):  
Genome Assembly ◽  
Bacterial Genome ◽  
Draft Genome ◽  
Coding Region ◽  
Entire Genome ◽  
Short Read ◽  
Short Reads ◽  
Repeat Structure ◽  
Short Read Sequence ◽  
Genome Assemblies

AbstractHigh-throughput comparative genomics has changed our view of bacterial evolution and relatedness. Many genomic comparisons, especially those regarding the accessory genome that is variably conserved across strains in a species, are performed using assembled genomes. For completed genomes, an assumption is made that the entire genome was incorporated into the genome assembly, while for draft assemblies, often constructed from short sequence reads, an assumption is made that genome assembly is an approximation of the entire genome. To understand the potential effects of short read assemblies on the estimation of the complete genome, we downloaded all completed bacterial genomes from GenBank, simulated short reads, assembled the simulated short reads and compared the resulting assembly to the completed assembly. Although most simulated assemblies demonstrated little reduction, others were reduced by as much as 25%, which was correlated with the repeat structure of the genome. A comparative analysis of lost coding region sequences demonstrated that up to 48 CDSs or up to ~112,000 bases of coding region sequence, were missing from some draft assemblies compared to their finished counterparts. Although this effect was observed to some extent in 32% of genomes, only minimal effects were observed on pan-genome statistics when using simulated draft genome assemblies. The benefits and limitations of using draft genome assemblies should be fully realized before interpreting data from assembly-based comparative analyses.

scholarly journals Improving PacBio Long Read Accuracy by Short Read Alignment

PLoS ONE ◽  
2012 ◽  
Vol 7 (10) ◽  
pp. e46679 ◽  
Author(s):  
Kin Fai Au ◽  
Jason G. Underwood ◽  
Lawrence Lee ◽  
Wing Hung Wong
Keyword(s):  
Short Read ◽  
Read Alignment ◽  
Short Read Alignment ◽  
Long Read ◽  
Read Accuracy

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 Fuzzy set intersection based paired-end short-read alignment

2021 ◽  
Author(s):  
William J Bolosky ◽  
Arun Subramaniyan ◽  
Matei Zaharia ◽  
Ravi Pandya ◽  
Taylor Sittler ◽  
...  
Keyword(s):  
Fuzzy Set ◽  
Genetic Material ◽  
Genomic Data ◽  
Short Read ◽  
Read Alignment ◽  
Short Read Alignment ◽  
Set Intersection

Much genomic data comes in the form of paired-end reads: two reads that represent genetic material with a small gap between. We present a new algorithm for aligning both reads in a pair simultaneously by fuzzily intersecting the sets of candidate alignment locations for each read. This algorithm is often much faster and produces alignments that result in variant calls having roughly the same concordance as the best competing aligners.

AligneR: A Process-in-Memory Architecture for Short Read Alignment in ReRAMs

2018 ◽  
Vol 17 (2) ◽  
pp. 237-240 ◽  
Author(s):  
Farzaneh Zokaee ◽  
Hamid R. Zarandi ◽  
Lei Jiang
Keyword(s):  
Memory Architecture ◽  
Short Read ◽  
Read Alignment ◽  
Short Read Alignment

scholarly journals ntJoin: Fast and lightweight assembly-guided scaffolding using minimizer graphs

2020 ◽  
Author(s):  
Lauren Coombe ◽  
Vladimir Nikolić ◽  
Justin Chu ◽  
Inanc Birol ◽  
René L. Warren
Keyword(s):  
Reference Sequence ◽  
Biological Research ◽  
Closely Related Species ◽  
Draft Assembly ◽  
Short Read ◽  
Sequencing Technologies ◽  
Long Read ◽  
Genome Assemblies ◽  
High Quality Genome ◽  
Reference Human Genome

AbstractSummaryThe ability to generate high-quality genome sequences is cornerstone to modern biological research. Even with recent advancements in sequencing technologies, many genome assemblies are still not achieving reference-grade. Here, we introduce ntJoin, a tool that leverages structural synteny between a draft assembly and reference sequence(s) to contiguate and correct the former with respect to the latter. Instead of alignments, ntJoin uses a lightweight mapping approach based on a graph data structure generated from ordered minimizer sketches. The tool can be used in a variety of different applications, including improving a draft assembly with a reference-grade genome, a short read assembly with a draft long read assembly, and a draft assembly with an assembly from a closely-related species. When scaffolding a human short read assembly using the reference human genome or a long read assembly, ntJoin improves the NGA50 length 23- and 13-fold, respectively, in under 13 m, using less than 11 GB of RAM. Compared to existing reference-guided assemblers, ntJoin generates highly contiguous assemblies faster and using less memory.Availability and implementationntJoin is written in C++ and Python, and is freely available at https://github.com/bcgsc/[email protected]

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.

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