scholarly journals A fully phased accurate assembly of an individual human genome

2019 ◽  
Author(s):  
David Porubsky ◽  
Peter Ebert ◽  
Peter A. Audano ◽  
Mitchell R. Vollger ◽  
William T. Harvey ◽  
...  
Keyword(s):  
Genome Assembly ◽  
De Novo ◽  
Consensus Sequence ◽  
Error Rates ◽  
Single Individual ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Consensus Sequences ◽  
Oxford Nanopore ◽  
Genome Assemblies

The prevailing genome assembly paradigm is to produce consensus sequences that “collapse” parental haplotypes into a consensus sequence. Here, we leverage the chromosome-wide phasing and scaffolding capabilities of single-cell strand sequencing (Strand-seq)1,2 and combine them with high-fidelity (HiFi) long sequencing reads3, in a novel reference-free workflow for diploid de novo genome assembly. Employing this strategy, we produce completely phased de novo genome assemblies separately for each haplotype of a single individual of Puerto Rican origin (HG00733) in the absence of parental data. The assemblies are accurate (QV > 40), highly contiguous (contig N50 > 25 Mbp) with low switch error rates (0.4%) providing fully phased single-nucleotide variants (SNVs), indels, and structural variants (SVs). A comparison of Oxford Nanopore and PacBio phased assemblies identifies 150 regions that are preferential sites of contig breaks irrespective of sequencing technology or phasing algorithms.

scholarly journals Sparc: a sparsity-based consensus algorithm for long erroneous sequencing reads

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2016 ◽  
Author(s):  
Chengxi Ye ◽  
Zhanshan (Sam) Ma
Keyword(s):  
Error Rate ◽  
Genome Assembly ◽  
De Novo ◽  
Consensus Sequence ◽  
Variant Calling ◽  
Error Rates ◽  
Consensus Algorithm ◽  
High Quality ◽  
Oxford Nanopore ◽  
Generation Sequencing

Motivation.The third generation sequencing (3GS) technology generates long sequences of thousands of bases. However, its current error rates are estimated in the range of 15–40%, significantly higher than those of the prevalent next generation sequencing (NGS) technologies (less than 1%). Fundamental bioinformatics tasks such asde novogenome assembly and variant calling require high-quality sequences that need to be extracted from these long but erroneous 3GS sequences.Results.We describe a versatile and efficient linear complexity consensus algorithm Sparc to facilitatede novogenome assembly. Sparc builds a sparse k-mer graph using a collection of sequences from a targeted genomic region. The heaviest path which approximates the most likely genome sequence is searched through a sparsity-induced reweighted graph as the consensus sequence. Sparc supports using NGS and 3GS data together, which leads to significant improvements in both cost efficiency and computational efficiency. Experiments with Sparc show that our algorithm can efficiently provide high-quality consensus sequences using both PacBio and Oxford Nanopore sequencing technologies. With only 30× PacBio data, Sparc can reach a consensus with error rate <0.5%. With the more challenging Oxford Nanopore data, Sparc can also achieve similar error rate when combined with NGS data. Compared with the existing approaches, Sparc[i] calculates the consensus with higher accuracy, uses 80% less memory and time, approximately. The source code is available for download athttps://github.com/yechengxi/Sparc.

scholarly journals Fully phased human genome assembly without parental data using single-cell strand sequencing and long reads

2020 ◽  
Author(s):  
David Porubsky ◽  
◽  
Peter Ebert ◽  
Peter A. Audano ◽  
Mitchell R. Vollger ◽  
...  
Keyword(s):  
Single Cell ◽  
Genome Assembly ◽  
De Novo ◽  
Error Rates ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
De Novo Genome Assembly ◽  
Parental Data ◽  
Human Genome Assembly ◽  
Long Read

AbstractHuman genomes are typically assembled as consensus sequences that lack information on parental haplotypes. Here we describe a reference-free workflow for diploid de novo genome assembly that combines the chromosome-wide phasing and scaffolding capabilities of single-cell strand sequencing1,2 with continuous long-read or high-fidelity3 sequencing data. Employing this strategy, we produced a completely phased de novo genome assembly for each haplotype of an individual of Puerto Rican descent (HG00733) in the absence of parental data. The assemblies are accurate (quality value > 40) and highly contiguous (contig N50 > 23 Mbp) with low switch error rates (0.17%), providing fully phased single-nucleotide variants, indels and structural variants. A comparison of Oxford Nanopore Technologies and Pacific Biosciences phased assemblies identified 154 regions that are preferential sites of contig breaks, irrespective of sequencing technology or phasing algorithms.

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 Pushing the limits of de novo genome assembly for complex prokaryotic genomes harboring very long, near identical repeats

2018 ◽  
Author(s):  
Michael Schmid ◽  
Daniel Frei ◽  
Andrea Patrignani ◽  
Ralph Schlapbach ◽  
Jürg E. Frey ◽  
...  
Keyword(s):  
Dark Matter ◽  
Genome Assembly ◽  
De Novo ◽  
Bacterial Genomes ◽  
De Novo Genome Assembly ◽  
Assembly Algorithm ◽  
Long Reads ◽  
Oxford Nanopore ◽  
Prokaryotic Genomes ◽  
Genome Assemblies

AbstractGenerating a complete, de novo genome assembly for prokaryotes is often considered a solved problem. However, we here show that Pseudomonas koreensis P19E3 harbors multiple, near identical repeat pairs up to 70 kilobase pairs in length. Beyond long repeats, the P19E3 assembly was further complicated by a shufflon region. Its complex genome could not be de novo assembled with long reads produced by Pacific Biosciences’ technology, but required very long reads from the Oxford Nanopore Technology. Another important factor for a full genomic resolution was the choice of assembly algorithm.Importantly, a repeat analysis indicated that very complex bacterial genomes represent a general phenomenon beyond Pseudomonas. Roughly 10% of 9331 complete bacterial and a handful of 293 complete archaeal genomes represented this dark matter for de novo genome assembly of prokaryotes. Several of these dark matter genome assemblies contained repeats far beyond the resolution of the sequencing technology employed and likely contain errors, other genomes were closed employing labor-intense steps like cosmid libraries, primer walking or optical mapping. Using very long sequencing reads in combination with assemblers capable of resolving long, near identical repeats will bring most prokaryotic genomes within reach of fast and complete de novo genome assembly.

scholarly journals Detecting and phasing minor single-nucleotide variants from long-read sequencing data

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Zhixing Feng ◽  
Jose C. Clemente ◽  
Brandon Wong ◽  
Eric E. Schadt
Keyword(s):  
Genetic Heterogeneity ◽  
Error Rates ◽  
Metagenomic Data ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Sequencing Technologies ◽  
Oxford Nanopore ◽  
Long Read ◽  
Technological Limitations

AbstractCellular genetic heterogeneity is common in many biological conditions including cancer, microbiome, and co-infection of multiple pathogens. Detecting and phasing minor variants play an instrumental role in deciphering cellular genetic heterogeneity, but they are still difficult tasks because of technological limitations. Recently, long-read sequencing technologies, including those by Pacific Biosciences and Oxford Nanopore, provide an opportunity to tackle these challenges. However, high error rates make it difficult to take full advantage of these technologies. To fill this gap, we introduce iGDA, an open-source tool that can accurately detect and phase minor single-nucleotide variants (SNVs), whose frequencies are as low as 0.2%, from raw long-read sequencing data. We also demonstrate that iGDA can accurately reconstruct haplotypes in closely related strains of the same species (divergence ≥0.011%) from long-read metagenomic data.

scholarly journals Optimizing experimental design for genome sequencing and assembly with Oxford Nanopore Technologies

2020 ◽  
Author(s):  
John M. Sutton ◽  
Janna L. Fierst
Keyword(s):  
Experimental Design ◽  
Genome Sequencing ◽  
Dna Sequences ◽  
Genome Assembly ◽  
De Novo ◽  
Error Rates ◽  
Oxford Nanopore ◽  
Broad Array ◽  
Sequencing Strategy ◽  
Oxford Nanopore Technologies

SummaryHigh quality reference genome sequences are the core of modern genomics. Oxford Nanopore Technologies (ONT) produces inexpensive DNA sequences in excess of 100,000 nucleotides but error rates remain >10% and assembling these sequences, particularly for eukaryotes, is a non-trivial problem. To date there has been no comprehensive attempt to generate experimental design for ONT genome sequencing and assembly. Here, we simulate ONT and Illumina DNA sequence reads for Escherichia coli, Caenorhabditis elegans, Arabidopsis thaliana, and Drosophila melanogaster. We quantify the influence of sequencing coverage, assembly software and experimental design on de novo genome assembly and error correction to predict the optimum sequencing strategy for these organisms. We show proof of concept using real ONT data generated for the nematode Caenorhabditis remanei. ONT sequencing is inexpensive and accessible, and our quantitative results will be helpful for a broad array of researchers seeking guidance for de novo genome assembly projects.

scholarly journals Detecting and phasing minor single-nucleotide variants from long-read sequencing data

2020 ◽  
Author(s):  
Zhixing Feng ◽  
Jose Clemente ◽  
Brandon Wong ◽  
Eric E. Schadt
Keyword(s):  
Genetic Heterogeneity ◽  
Error Rates ◽  
Metagenomic Data ◽  
Significant Advance ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Sequencing Technologies ◽  
Oxford Nanopore ◽  
Long Read

AbstractCellular genetic heterogeneity is common in many biological conditions including cancer, microbiome, co-infection of multiple pathogens. Detecting and phasing minor variants, which is to determine whether multiple variants are from the same haplotype, play an instrumental role in deciphering cellular genetic heterogeneity, but are still difficult because of technological limitations. Recently, long-read sequencing technologies, including those by Pacific Biosciences and Oxford Nanopore, have provided an unprecedented opportunity to tackle these challenges. However, high error rates make it difficult to take full advantage of these technologies. To fill this gap, we introduce iGDA, an open-source tool that can accurately detect and phase minor single-nucleotide variants (SNVs), whose frequencies are as low as 0.2%, from raw long-read sequencing data. We also demonstrated that iGDA can accurately reconstruct haplotypes in closely-related strains of the same species (divergence ≥ 0.011%) from long-read metagenomic data. Our approach, therefore, presents a significant advance towards the complete deciphering of cellular genetic heterogeneity.

scholarly journals De novo Nanopore read quality improvement using deep learning

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Nathan LaPierre ◽  
Rob Egan ◽  
Wei Wang ◽  
Zhong Wang
Keyword(s):  
Error Correction ◽  
Genome Assembly ◽  
Large Scale ◽  
De Novo ◽  
Error Rates ◽  
De Novo Genome Assembly ◽  
Sequencing Technologies ◽  
Oxford Nanopore ◽  
Long Read ◽  
Read Error Correction

Abstract Background Long read sequencing technologies such as Oxford Nanopore can greatly decrease the complexity of de novo genome assembly and large structural variation identification. Currently Nanopore reads have high error rates, and the errors often cluster into low-quality segments within the reads. The limited sensitivity of existing read-based error correction methods can cause large-scale mis-assemblies in the assembled genomes, motivating further innovation in this area. Results Here we developed a Convolutional Neural Network (CNN) based method, called MiniScrub, for identification and subsequent “scrubbing” (removal) of low-quality Nanopore read segments to minimize their interference in downstream assembly process. MiniScrub first generates read-to-read overlaps via MiniMap2, then encodes the overlaps into images, and finally builds CNN models to predict low-quality segments. Applying MiniScrub to real world control datasets under several different parameters, we show that it robustly improves read quality, and improves read error correction in the metagenome setting. Compared to raw reads, de novo genome assembly with scrubbed reads produces many fewer mis-assemblies and large indel errors. Conclusions MiniScrub is able to robustly improve read quality of Oxford Nanopore reads, especially in the metagenome setting, making it useful for downstream applications such as de novo assembly. We propose MiniScrub as a tool for preprocessing Nanopore reads for downstream analyses. MiniScrub is open-source software and is available at https://bitbucket.org/berkeleylab/jgi-miniscrub.

scholarly journals MiniScrub: de novo long read scrubbing using approximate alignment and deep learning

2018 ◽  
Author(s):  
Nathan LaPierre ◽  
Rob Egan ◽  
Wei Wang ◽  
Zhong Wang
Keyword(s):  
Open Source Software ◽  
Genome Assembly ◽  
Large Scale ◽  
Structural Variation ◽  
De Novo ◽  
Error Rates ◽  
Sequencing Technologies ◽  
Oxford Nanopore ◽  
Long Read ◽  
Reference Genomes

AbstractLong read sequencing technologies such as Oxford Nanopore can greatly de-crease the complexity of de novo genome assembly and large structural variation iden-tification. Currently Nanopore reads have high error rates, and the errors often cluster into low-quality segments within the reads. Many methods for resolving these errors require access to reference genomes, high-fidelity short reads, or reference genomes, which are often not available. De novo error correction modules are available, often as part of assembly tools, but large-scale errors still remain in resulting assemblies, motivating further innovation in this area. We developed a novel Convolutional Neu-ral Network (CNN) based method, called MiniScrub, for de novo identification and subsequent “scrubbing” (removal) of low-quality Nanopore read segments. MiniScrub first generates read-to-read alignments by MiniMap, then encodes the alignments into images, and finally builds CNN models to predict low-quality segments that could be scrubbed based on a customized quality cutoff. Applying MiniScrub to real world con-trol datasets under several different parameters, we show that it robustly improves read quality. Compared to raw reads, de novo genome assembly with scrubbed reads pro-duces many fewer mis-assemblies and large indel errors. We propose MiniScrub as a tool for preprocessing Nanopore reads for downstream analyses. MiniScrub is open-source software and is available at https://bitbucket.org/berkeleylab/jgi-miniscrub

scholarly journals SARS-CoV-2 genomic analyses in cancer patients reveal elevated intrahost genetic diversity

2021 ◽  
Author(s):  
Juliana D Siqueira ◽  
Livia R Goes ◽  
Brunna M Alves ◽  
Pedro S de Carvalho ◽  
Claudia Cicala ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Phylogenetic Analysis ◽  
Cancer Patients ◽  
Disease Severity ◽  
Healthcare Workers ◽  
Viral Population ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Consensus Sequences ◽  
Vulnerable Patients

Abstract Numerous factors have been identified to influence susceptibility to SARS-CoV-2 infection and disease severity. Cancer patients are more prone to clinically evolve to more severe COVID-19 conditions, but the determinants of such a more severe outcome remain largely unknown. We have determined the full-length SARS-CoV-2 genomic sequences of cancer patients and healthcare workers (non-cancer controls) by deep sequencing and investigated the within-host viral population of each infection, quantifying intrahost genetic diversity. Naso- and oropharyngeal SARS-CoV-2+ swabs from 57 cancer patients and 14 healthcare workers from the Brazilian National Cancer Institute were collected in April–May 2020. Complete genome amplification using ARTIC network V3 multiplex primers was performed followed by next-generation sequencing. Assemblies were conducted in Geneious R11, where consensus sequences were extracted and intrahost single nucleotide variants were identified. Maximum likelihood phylogenetic analysis was performed using PhyMLv.3.0 and lineages were classified using Pangolin and CoV-GLUE. Phylogenetic analysis showed that all but one strain belonged to clade B1.1. Four genetically linked mutations known as the globally dominant SARS-CoV-2 haplotype (C241T, C3037T, C14408T and A23403G) were found in the majority of consensus sequences. SNV signatures of previously characterized Brazilian genomes were also observed in most samples. Another 85 SNVs were found at a lower frequency (1.4-19.7%) among the consensus sequences. Cancer patients displayed a significantly higher intrahost viral genetic diversity compared to healthcare workers. This difference was independent of SARS-CoV-2 Ct values obtained at the diagnostic tests, which did not differ between the two groups. The most common nucleotide changes of intrahost SNVs in both groups were consistent with APOBEC and ADAR activities. Intrahost genetic diversity in cancer patients was not associated with disease severity, use of corticosteroids, or use of antivirals, characteristics that could influence viral diversity. Moreover, the presence of metastasis, either in general or specifically in the lung, was not associated with intrahost diversity among cancer patients. Cancer patients carried significantly higher numbers of minor variants compared to non-cancer counterparts. Further studies on SARS-CoV-2 diversity in especially vulnerable patients will shed light onto the understanding of the basis of COVID-19 different outcomes in humans.

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