scholarly journals A reference bacterial genome dataset generated on the MinION™ portable single-molecule nanopore sequencer

2014 ◽  
Author(s):  
Josh Quick ◽  
Aaron Quinlan ◽  
Nicholas Loman
Keyword(s):  
Single Molecule ◽  
De Novo ◽  
Sequence Data ◽  
Bacterial Genome ◽  
Model Organism ◽  
Variant Calling ◽  
Laptop Computer ◽  
Early Access ◽  
Dna Strands ◽  
K 12

Background: The MinION™ is a new, portable single-molecule sequencer developed by Oxford Nanopore Technologies. It measures four inches in length and is powered from the USB 3.0 port of a laptop computer. By measuring the change in current produced when DNA strands translocate through and interact with a charged protein nanopore the device is able to deduce the underlying nucleotide sequence. Findings: We present a read dataset from whole-genome shotgun sequencing of the model organism Escherichia coli K-12 substr. MG1655 generated on a MinION™ device during the early-access MinION Access Program (MAP). Sequencing runs of the MinION™ are presented, one generated using R7 chemistry (released in July 2014) and one using R7.3 (released in September 2014). Conclusions: Base-called sequence data are provided to demonstrate the nature of data produced by the MinION™ platform and to encourage the development of customised methods for alignment, consensus and variant calling, de novo assembly and scaffolding. FAST5 files containing event data within the HDF5 container format are provided to assist with the development of improved base-calling methods. Datasets are provided through the GigaDB database at http://gigadb.org/dataset/100102

scholarly journals Decona: From demultiplexing to consensus for Nanopore amplicon data

2021 ◽  
Vol 4 ◽  
Author(s):  
Saskia Oosterbroek ◽  
Karlijn Doorenspleet ◽  
Reindert Nijland ◽  
Lara Jansen
Keyword(s):  
Sequence Data ◽  
Variant Calling ◽  
Environmental Dna ◽  
Laptop Computer ◽  
Consensus Sequences ◽  
Sequencing Errors ◽  
Blast Output ◽  
Command Line Tool ◽  
Microbial Symbionts ◽  
User Friendly

Sequencing of long amplicons is one of the major benefits of Nanopore technologies, as it allows for reads much longer than Illumina. One of the major challenges for the analysis of these long Nanopore reads is the relatively high error rate. Sequencing errors are generally corrected by consensus generation and polishing. This is still a challenge for mixed samples such as metabarcoding environmental DNA, bulk DNA, mixed amplicon PCR’s and contaminated samples because sequence data would have to be clustered before consensus generation. To this end, we developed Decona (https://github.com/Saskia-Oosterbroek/decona), a command line tool that creates consensus sequences from mixed (metabarcoding) samples using a single command. Decona uses the CD-hit algorithm to cluster reads after demultiplexing (qcat) and filtering (NanoFilt). The sequences in each cluster are subsequently aligned (Minimap2), consensus sequences are generated (Racon) and finally polished (Medaka). Variant calling of the clusters (Medaka) is optional. With the integration of the BLAST+ application Decona does not only generate consensus sequences but also produces BLAST output if desired. The program can be used on a laptop computer making it suitable for use under field conditions. Amplicon data ranging from 300-7500 nucleotides was successfully processed by Decona, creating consensus sequences reaching over 99,9% read identity. This included fish datasets (environmental DNA from filtered water) from a curated aquarium, vertebrate datasets that were contaminated with human sequences and separating sponge sequences from their countless microbial symbionts. Decona considerably simplifies and speeds up post sequencing processes, providing consensus sequences and BLAST output through a single command. Classifying consensus sequences instead of raw sequences improves classification accuracy and drastically decreases the amount of sequences that need to be classified. Overall it is a user friendly option for researchers with limited knowledge of script based data processing.

scholarly journals Haplotype-aware variant calling enables high accuracy in nanopore long-reads using deep neural networks

2021 ◽  
Author(s):  
Kishwar Shafin ◽  
Trevor Pesout ◽  
Pi-Chuan Chang ◽  
Maria Nattestad ◽  
Alexey Kolesnikov ◽  
...  
Keyword(s):  
De Novo ◽  
Sequence Data ◽  
Variant Calling ◽  
High Accuracy ◽  
Superior Performance ◽  
Read Length ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Short Read ◽  
Long Read

Long-read sequencing has the potential to transform variant detection by reaching currently difficult-to-map regions and routinely linking together adjacent variations to enable read based phasing. Third-generation nanopore sequence data has demonstrated a long read length, but current interpretation methods for its novel pore-based signal have unique error profiles, making accurate analysis challenging. Here, we introduce a haplotype-aware variant calling pipeline PEPPER-Margin-DeepVariant that produces state-of-the-art variant calling results with nanopore data. We show that our nanopore-based method outperforms the short-read-based single nucleotide variant identification method at the whole genome-scale and produces high-quality single nucleotide variants in segmental duplications and low-mappability regions where short-read based genotyping fails. We show that our pipeline can provide highly-contiguous phase blocks across the genome with nanopore reads, contiguously spanning between 85% to 92% of annotated genes across six samples. We also extend PEPPER-Margin-DeepVariant to PacBio HiFi data, providing an efficient solution with superior performance than the current WhatsHap-DeepVariant standard. Finally, we demonstrate de novo assembly polishing methods that use nanopore and PacBio HiFi reads to produce diploid assemblies with high accuracy (Q35+ nanopore-polished and Q40+ PacBio-HiFi-polished).

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 AsmMix: A pipeline for high quality diploid de novo assembly

2021 ◽  
Author(s):  
Pei Wu ◽  
Chao Liu ◽  
Ou Wang ◽  
Xia Zhao ◽  
Fang Chen ◽  
...  
Keyword(s):  
Single Molecule ◽  
De Novo ◽  
Variant Calling ◽  
The Other ◽  
Second Step ◽  
Small Scale ◽  
Mixing Process ◽  
High Quality ◽  
Single Molecule Sequencing ◽  
Long Read

AbstractIn this paper, we report a pipeline, AsmMix, which is capable of producing both contiguous and high-quality diploid genomes. The pipeline consists of two steps. In the first step, two sets of assemblies are generated: one is based on co-barcoded reads, which are highly accurate and haplotype-resolved but contain many gaps, the other assembly is based on single-molecule sequencing reads, which is contiguous but error-prone. In the second step, those two sets of assemblies are compared and integrated into a haplotype-resolved assembly with fewer errors. We test our pipeline using a dataset of human genome NA24385, perform variant calling from those assemblies and then compare against GIAB Benchmark. We show that AsmMix pipeline could produce highly contiguous, accurate, and haplotype-resolved assemblies. Especially the assembly mixing process could effectively reduce small-scale errors in the long read assembly.

scholarly journals Improved assembly and variant detection of a haploid human genome using single-molecule, high-fidelity long reads

2019 ◽  
Author(s):  
Mitchell R. Vollger ◽  
Glennis A. Logsdon ◽  
Peter A. Audano ◽  
Arvis Sulovari ◽  
David Porubsky ◽  
...  
Keyword(s):  
Human Genome ◽  
Single Molecule ◽  
Tandem Repeats ◽  
De Novo ◽  
Sequence Data ◽  
Gene Annotation ◽  
Hydatidiform Mole ◽  
High Fidelity ◽  
Human Genomes ◽  
Long Read

AbstractThe sequence and assembly of human genomes using long-read sequencing technologies has revolutionized our understanding of structural variation and genome organization. We compared the accuracy, continuity, and gene annotation of genome assemblies generated from either high-fidelity (HiFi) or continuous long-read (CLR) datasets from the same complete hydatidiform mole human genome. We find that the HiFi sequence data assemble an additional 10% of duplicated regions and more accurately represent the structure of tandem repeats, as validated with orthogonal analyses. As a result, an additional 5 Mbp of pericentromeric sequences are recovered in the HiFi assembly, resulting in a 2.5-fold increase in the NG50 within 1 Mbp of the centromere (HiFi 480.6 kbp, CLR 191.5 kbp). Additionally, the HiFi genome assembly was generated in significantly less time with fewer computational resources than the CLR assembly. Although the HiFi assembly has significantly improved continuity and accuracy in many complex regions of the genome, it still falls short of the assembly of centromeric DNA and the largest regions of segmental duplication using existing assemblers. Despite these shortcomings, our results suggest that HiFi may be the most effective stand-alone technology for de novo assembly of human genomes.

scholarly journals High contiguity de novo genome assembly and DNA modification analyses for the fungus fly, Sciara coprophila, using single-molecule sequencing

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
John M. Urban ◽  
Michael S. Foulk ◽  
Jacob E. Bliss ◽  
C. Michelle Coleman ◽  
Nanyan Lu ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Single Molecule ◽  
De Novo ◽  
Bacterial Genome ◽  
Draft Genome ◽  
Dna Amplification ◽  
Chromosome Elimination ◽  
Paternal Chromosome ◽  
De Novo Genome Assembly ◽  
Long Read

Abstract Background The lower Dipteran fungus fly, Sciara coprophila, has many unique biological features that challenge the rule of genome DNA constancy. For example, Sciara undergoes paternal chromosome elimination and maternal X chromosome nondisjunction during spermatogenesis, paternal X elimination during embryogenesis, intrachromosomal DNA amplification of DNA puff loci during larval development, and germline-limited chromosome elimination from all somatic cells. Paternal chromosome elimination in Sciara was the first observation of imprinting, though the mechanism remains a mystery. Here, we present the first draft genome sequence for Sciara coprophila to take a large step forward in addressing these features. Results We assembled the Sciara genome using PacBio, Nanopore, and Illumina sequencing. To find an optimal assembly using these datasets, we generated 44 short-read and 50 long-read assemblies. We ranked assemblies using 27 metrics assessing contiguity, gene content, and dataset concordance. The highest-ranking assemblies were scaffolded using BioNano optical maps. RNA-seq datasets from multiple life stages and both sexes facilitated genome annotation. A set of 66 metrics was used to select the first draft assembly for Sciara. Nearly half of the Sciara genome sequence was anchored into chromosomes, and all scaffolds were classified as X-linked or autosomal by coverage. Conclusions We determined that X-linked genes in Sciara males undergo dosage compensation. An entire bacterial genome from the Rickettsia genus, a group known to be endosymbionts in insects, was co-assembled with the Sciara genome, opening the possibility that Rickettsia may function in sex determination in Sciara. Finally, the signal level of the PacBio and Nanopore data support the presence of cytosine and adenine modifications in the Sciara genome, consistent with a possible role in imprinting.

Glutton: large-scale integration of non-model organism transcriptome data for comparative analysis

2016 ◽  
Author(s):  
Alan Medlar ◽  
Laura Laakso ◽  
Andreia Miraldo ◽  
Ari Löytynoja
Keyword(s):  
Comparative Analysis ◽  
Large Scale ◽  
De Novo ◽  
Sequence Data ◽  
Model Organism ◽  
Model Organisms ◽  
Rna Seq ◽  
Reference Species ◽  
Wide Range ◽  
The Impact

AbstractHigh-throughput RNA-seq data has become ubiquitous in the study of non-model organisms, but its use in comparative analysis remains a challenge. Without a reference genome for mapping, sequence data has to be de novo assembled, producing large numbers of short, highly redundant contigs. Preparing these assemblies for comparative analyses requires the removal of redundant isoforms, assignment of orthologs and converting fragmented transcripts into gene alignments. In this article we present Glutton, a novel tool to process transcriptome assemblies for downstream evolutionary analyses. Glutton takes as input a set of fragmented, possibly erroneous transcriptome assemblies. Utilising phylogeny-aware alignment and reference data from a closely related species, it reconstructs one transcript per gene, finds orthologous sequences and produces accurate multiple alignments of coding sequences. We present a comprehensive analysis of Glutton’s performance across a wide range of divergence times between study and reference species. We demonstrate the impact choice of assembler has on both the number of alignments and the correctness of ortholog assignment and show substantial improvements over heuristic methods, without sacrificing correctness. Finally, using inference of Darwinian selection as an example of downstream analysis, we show that Glutton-processed RNA-seq data give results comparable to those obtained from full length gene sequences even with distantly related reference species. Glutton is available from http://wasabiapp.org/software/glutton/ and is licensed under the GPLv3.

scholarly journals Efficient long single molecule sequencing for cost effective and accurate sequencing, haplotyping, and de novo assembly

2018 ◽  
Author(s):  
Ou Wang ◽  
Robert Chin ◽  
Xiaofang Cheng ◽  
Michelle Ka Wu ◽  
Qing Mao ◽  
...  
Keyword(s):  
Single Molecule ◽  
Genome Assembly ◽  
De Novo ◽  
Low Cost ◽  
Variant Calling ◽  
Cost Effective ◽  
High Quality ◽  
Single Molecule Sequencing ◽  
Single Tube ◽  
Complex Structural

Obtaining accurate sequences from long DNA molecules is very important for genome assembly and other applications. Here we describe single tube long fragment read (stLFR), a technology that enables this a low cost. It is based on adding the same barcode sequence to sub-fragments of the original long DNA molecule (DNA co-barcoding). To achieve this efficiently, stLFR uses the surface of microbeads to create millions of miniaturized barcoding reactions in a single tube. Using a combinatorial process up to 3.6 billion unique barcode sequences were generated on beads, enabling practically non-redundant co-barcoding with 50 million barcodes per sample. Using stLFR, we demonstrate efficient unique co-barcoding of over 8 million 20-300 kb genomic DNA fragments. Analysis of the genome of the human genome NA12878 with stLFR demonstrated high quality variant calling and phasing into contigs up to N50 34 Mb. We also demonstrate detection of complex structural variants and complete diploid de novo assembly of NA12878. These analyses were all performed using single stLFR libraries and their construction did not significantly add to the time or cost of whole genome sequencing (WGS) library preparation. stLFR represents an easily automatable solution that enables high quality sequencing, phasing, SV detection, scaffolding, cost-effective diploid de novo genome assembly, and other long DNA sequencing applications.

scholarly journals Variant calling for cpn60 barcode sequence-based microbiome profiling

2019 ◽  
Author(s):  
Sarah J. Vancuren ◽  
Scott J. Dos Santos ◽  
Janet E. Hill ◽  
Keyword(s):  
De Novo ◽  
Sequence Data ◽  
Variant Calling ◽  
Taxonomic Composition ◽  
Species Level ◽  
Reference Sequence ◽  
Sequence Length ◽  
Sequence Variant ◽  
Operational Taxonomic Units ◽  
Microbiome Profiling

AbstractAmplification and sequencing of conserved genetic barcodes such as the cpn60 gene is a common approach to determining the taxonomic composition of microbiomes. Exact sequence variant calling has been proposed as an alternative to previously established methods for aggregation of sequence reads into operational taxonomic units (OTU). We investigated the utility of variant calling for cpn60 barcode sequences and determined the minimum sequence length required to provide species-level resolution. Sequence data from the 5’ region of the cpn60 barcode amplified from the human vaginal microbiome (n=45), and a mock community were used to compare variant calling to de novo assembly of reads, and mapping to a reference sequence database in terms of number of OTU formed, and overall community composition. Variant calling resulted in microbiome profiles that were consistent in apparent composition to those generated with the other methods but with significant logistical advantages. Variant calling is rapid, achieves high resolution of taxa, and does not require reference sequence data. Our results further demonstrate that 150 bp from the 5’ end of the cpn60 barcode sequence is sufficient to provide species-level resolution of microbiota.

scholarly journals DeepTrio: Variant Calling in Families Using Deep Learning

2021 ◽  
Author(s):  
Alexey Kolesnikov ◽  
Sidharth Goel ◽  
Maria Nattestad ◽  
Taedong Yun ◽  
Gunjan Baid ◽  
...  
Keyword(s):  
Deep Learning ◽  
De Novo ◽  
Sequence Data ◽  
Genetic Diseases ◽  
Variant Calling ◽  
Training Data ◽  
Sequencing Error ◽  
Sequence Information ◽  
Genome Context ◽  
Parental Inheritance

Every human inherits one copy of the genome from their mother and another from their father. Parental inheritance helps us understand the transmission of traits and genetic diseases, which often involve de novo variants and rare recessive alleles. Here we present DeepTrio, which learns to analyze child-mother-father trios from the joint sequence information, without explicit encoding of inheritance priors. DeepTrio learns how to weigh sequencing error, mapping error, and de novo rates and genome context directly from the sequence data. DeepTrio has higher accuracy on both Illumina and PacBio HiFi data when compared to DeepVariant. Improvements are especially pronounced at lower coverages (with 20x DeepTrio roughly equivalent to 30x DeepVariant). As DeepTrio learns directly from data, we also demonstrate extensions to exome calling solely by changing the training data. DeepTrio includes pre-trained models for Illumina WGS, Illumina exome, and PacBio HiFi.

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