A Computational Toolset for Rapid Identification of SARS-CoV-2, other Viruses, and Microorganisms from Sequencing Data

ABSTRACTIn this paper, we present a toolset and related resources for rapid identification of viruses and microorganisms from short-read or long-read sequencing data. We present fastv as an ultra-fast tool to detect microbial sequences present in sequencing data, identify target microorganisms, and visualize coverage of microbial genomes. This tool is based on the k-mer mapping and extension method. K-mer sets are generated by UniqueKMER, another tool provided in this toolset. UniqueKMER can generate complete sets of unique k-mers for each genome within a large set of viral or microbial genomes. For convenience, unique k-mers for microorganisms and common viruses that afflict humans have been generated and are provided with the tools. As a lightweight tool, fastv accepts FASTQ data as input, and directly outputs the results in both HTML and JSON formats. Prior to the k-mer analysis, fastv automatically performs adapter trimming, quality pruning, base correction, and other pre-processing to ensure the accuracy of k-mer analysis. Specifically, fastv provides built-in support for rapid SARS-CoV-2 identification and typing. Experimental results showed that fastv achieved 100% sensitivity and 100% specificity for detecting SARS-CoV-2 from sequencing data; and can distinguish SARS-CoV-2 from SARS, MERS, and other coronaviruses. This toolset is available at: https://github.com/OpenGene/fastv.

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A computational toolset for rapid identification of SARS-CoV-2, other viruses and microorganisms from sequencing data

Briefings in Bioinformatics ◽

10.1093/bib/bbaa231 ◽

2020 ◽

Cited By ~ 1

Author(s):

Shifu Chen ◽

Changshou He ◽

Yingqiang Li ◽

Zhicheng Li ◽

Charles E Melançon

Keyword(s):

Middle East ◽

Severe Acute Respiratory Syndrome ◽

Rapid Identification ◽

Large Set ◽

Sequencing Data ◽

Short Read ◽

Microbial Genomes ◽

Extension Method ◽

Long Read ◽

Adapter Trimming

Abstract In this paper, we present a toolset and related resources for rapid identification of viruses and microorganisms from short-read or long-read sequencing data. We present fastv as an ultra-fast tool to detect microbial sequences present in sequencing data, identify target microorganisms and visualize coverage of microbial genomes. This tool is based on the k-mer mapping and extension method. K-mer sets are generated by UniqueKMER, another tool provided in this toolset. UniqueKMER can generate complete sets of unique k-mers for each genome within a large set of viral or microbial genomes. For convenience, unique k-mers for microorganisms and common viruses that afflict humans have been generated and are provided with the tools. As a lightweight tool, fastv accepts FASTQ data as input and directly outputs the results in both HTML and JSON formats. Prior to the k-mer analysis, fastv automatically performs adapter trimming, quality pruning, base correction and other preprocessing to ensure the accuracy of k-mer analysis. Specifically, fastv provides built-in support for rapid severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) identification and typing. Experimental results showed that fastv achieved 100% sensitivity and 100% specificity for detecting SARS-CoV-2 from sequencing data; and can distinguish SARS-CoV-2 from SARS, Middle East respiratory syndrome and other coronaviruses. This toolset is available at: https://github.com/OpenGene/fastv.

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Comprehensive identification of transposable element insertions using multiple sequencing technologies

Nature Communications ◽

10.1038/s41467-021-24041-8 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Chong Chu ◽

Rebeca Borges-Monroy ◽

Vinayak V. Viswanadham ◽

Soohyun Lee ◽

Heng Li ◽

...

Keyword(s):

Transposable Element ◽

Structure And Function ◽

Endogenous Retroviruses ◽

Whole Genome Sequencing Data ◽

Whole Genome ◽

Sequencing Data ◽

Short Read ◽

Sequencing Technologies ◽

Long Read ◽

And Function

AbstractTransposable elements (TEs) help shape the structure and function of the human genome. When inserted into some locations, TEs may disrupt gene regulation and cause diseases. Here, we present xTea (x-Transposable element analyzer), a tool for identifying TE insertions in whole-genome sequencing data. Whereas existing methods are mostly designed for short-read data, xTea can be applied to both short-read and long-read data. Our analysis shows that xTea outperforms other short read-based methods for both germline and somatic TE insertion discovery. With long-read data, we created a catalogue of polymorphic insertions with full assembly and annotation of insertional sequences for various types of retroelements, including pseudogenes and endogenous retroviruses. Notably, we find that individual genomes have an average of nine groups of full-length L1s in centromeres, suggesting that centromeres and other highly repetitive regions such as telomeres are a significant yet unexplored source of active L1s. xTea is available at https://github.com/parklab/xTea.

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The long and the short of it: unlocking nanopore long-read RNA sequencing data with short-read differential expression analysis tools

NAR Genomics and Bioinformatics ◽

10.1093/nargab/lqab028 ◽

2021 ◽

Vol 3 (2) ◽

Author(s):

Xueyi Dong ◽

Luyi Tian ◽

Quentin Gouil ◽

Hasaru Kariyawasam ◽

Shian Su ◽

...

Keyword(s):

Differential Expression ◽

Expression Analysis ◽

Differential Expression Analysis ◽

Transcriptomic Analysis ◽

Statistical Testing ◽

Rna Seq ◽

Sequencing Data ◽

Short Read ◽

Sequencing Platform ◽

Long Read

Abstract Application of Oxford Nanopore Technologies’ long-read sequencing platform to transcriptomic analysis is increasing in popularity. However, such analysis can be challenging due to the high sequence error and small library sizes, which decreases quantification accuracy and reduces power for statistical testing. Here, we report the analysis of two nanopore RNA-seq datasets with the goal of obtaining gene- and isoform-level differential expression information. A dataset of synthetic, spliced, spike-in RNAs (‘sequins’) as well as a mouse neural stem cell dataset from samples with a null mutation of the epigenetic regulator Smchd1 was analysed using a mix of long-read specific tools for preprocessing together with established short-read RNA-seq methods for downstream analysis. We used limma-voom to perform differential gene expression analysis, and the novel FLAMES pipeline to perform isoform identification and quantification, followed by DRIMSeq and limma-diffSplice (with stageR) to perform differential transcript usage analysis. We compared results from the sequins dataset to the ground truth, and results of the mouse dataset to a previous short-read study on equivalent samples. Overall, our work shows that transcriptomic analysis of long-read nanopore data using long-read specific preprocessing methods together with short-read differential expression methods and software that are already in wide use can yield meaningful results.

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Rapid Mycobacterium tuberculosis spoligotyping from uncorrected long reads using Galru

10.1101/2020.05.31.126490 ◽

2020 ◽

Author(s):

Andrew J. Page ◽

Nabil-Fareed Alikhan ◽

Michael Strinden ◽

Thanh Le Viet ◽

Timofey Skvortsov

Keyword(s):

Mycobacterium Tuberculosis ◽

State Of The Art ◽

Sequence Data ◽

Human Pathogen ◽

Sequencing Data ◽

Short Read ◽

Short Read Sequencing ◽

Long Reads ◽

Long Read

AbstractSpoligotyping of Mycobacterium tuberculosis provides a subspecies classification of this major human pathogen. Spoligotypes can be predicted from short read genome sequencing data; however, no methods exist for long read sequence data such as from Nanopore or PacBio. We present a novel software package Galru, which can rapidly detect the spoligotype of a Mycobacterium tuberculosis sample from as little as a single uncorrected long read. It allows for near real-time spoligotyping from long read data as it is being sequenced, giving rapid sample typing. We compare it to the existing state of the art software and find it performs identically to the results obtained from short read sequencing data. Galru is freely available from https://github.com/quadram-institute-bioscience/galru under the GPLv3 open source licence.

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Complete Genome Sequence of Rubrobacter xylanophilus Strain AA3-22, Isolated from Arima Onsen in Japan

Microbiology Resource Announcements ◽

10.1128/mra.00818-19 ◽

2019 ◽

Vol 8 (34) ◽

Cited By ~ 1

Author(s):

Natsuki Tomariguchi ◽

Kentaro Miyazaki

Keyword(s):

Genome Sequence ◽

Complete Genome Sequence ◽

Complete Genome ◽

Hot Spring ◽

Sequencing Data ◽

Short Read ◽

Content Type ◽

Short Read Sequencing ◽

Oxford Nanopore ◽

Long Read

Rubrobacter xylanophilus strain AA3-22, belonging to the phylum Actinobacteria, was isolated from nonvolcanic Arima Onsen (hot spring) in Japan. Here, we report the complete genome sequence of this organism, which was obtained by combining Oxford Nanopore long-read and Illumina short-read sequencing data.

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LinkedSV for detection of mosaic structural variants from linked-read exome and genome sequencing data

10.1101/409789 ◽

2018 ◽

Cited By ~ 2

Author(s):

Li Fang ◽

Charlly Kao ◽

Michael V Gonzalez ◽

Fernanda A Mafra ◽

Renata Pellegrino da Silva ◽

...

Keyword(s):

Exome Sequencing ◽

Read Depth ◽

Structural Variants ◽

Sequencing Data ◽

High Coverage ◽

Short Read ◽

Short Read Sequencing ◽

Sequencing Studies ◽

Long Read ◽

Local Assembly

AbstractLinked-read sequencing provides long-range information on short-read sequencing data by barcoding reads originating from the same DNA molecule, and can improve the detection and breakpoint identification for structural variants (SVs). We present LinkedSV for SV detection on linked-read sequencing data. LinkedSV considers barcode overlapping and enriched fragment endpoints as signals to detect large SVs, while it leverages read depth, paired-end signals and local assembly to detect small SVs. Benchmarking studies demonstrates that LinkedSV outperforms existing tools, especially on exome data and on somatic SVs with low variant allele frequencies. We demonstrate clinical cases where LinkedSV identifies disease causal SVs from linked-read exome sequencing data missed by conventional exome sequencing, and show examples where LinkedSV identifies SVs missed by high-coverage long-read sequencing. In summary, LinkedSV can detect SVs missed by conventional short-read and long-read sequencing approaches, and may resolve negative cases from clinical genome/exome sequencing studies.

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Resolving the complex Bordetella pertussis genome using barcoded nanopore sequencing

10.1101/381640 ◽

2018 ◽

Author(s):

Natalie Ring ◽

Jonathan Abrahams ◽

Miten Jain ◽

Hugh Olsen ◽

Andrew Preston ◽

...

Keyword(s):

Bordetella Pertussis ◽

Flow Cell ◽

Nanopore Sequencing ◽

Library Preparation ◽

Genome Sequences ◽

Short Read ◽

Link Type ◽

Analysis Tools ◽

Long Read ◽

Assembly Pipeline

ABSTRACTThe genome of Bordetella pertussis is complex, with high GC content and many repeats, each longer than 1,000 bp. Short-read DNA sequencing is unable to resolve the structure of the genome; however, long-read sequencing offers the opportunity to produce single-contig B. pertussis assemblies using sequencing reads which are longer than the repetitive sections. We used an R9.4 MinION flow cell and barcoding to sequence five B. pertussis strains in a single sequencing run. We then trialled combinations of the many nanopore-user-community-built long-read analysis tools to establish the current optimal assembly pipeline for B. pertussis genome sequences. Our best long-read-only assemblies were produced by Canu read correction followed by assembly with Flye and polishing with Nanopolish, whilst the best hybrids (using nanopore and Illumina reads together) were produced by Canu correction followed by Unicycler. This pipeline produced closed genome sequences for four strains, revealing inter-strain genomic rearrangement. However, read mapping to the Tohama I reference genome suggests that the remaining strain contains an ultra-long duplicated region (over 100 kbp), which was not resolved by our pipeline. We have therefore demonstrated the ability to resolve the structure of several B. pertussis strains per single barcoded nanopore flow cell, but the genomes with highest complexity (e.g. very large duplicated regions) remain only partially resolved using the standard library preparation and will require an alternative library preparation method. For full strain characterisation, we recommend hybrid assembly of long and short reads together; for comparison of genome arrangement, assembly using long reads alone is sufficient.DATA SUMMARYFinal sequence read files (fastq) for all 5 strains have been deposited in the SRA, BioProject PRJNA478201, accession numbers SAMN09500966, SAMN09500967, SAMN09500968, SAMN09500969, SAMN09500970A full list of accession numbers for Illumina sequence reads is available in Table S1Assembly tests, basecalled read sets and reference materials are available from figshare: https://figshare.com/projects/Resolving_the_complex_Bordetella_pertussis_genome_using_barcoded_nanopore_sequencing/31313Genome sequences for B. pertussis strains UK36, UK38, UK39, UK48 and UK76 have been deposited in GenBank; accession numbers: CP031289, CP031112, CP031113, QRAX00000000, CP031114Source code and full commands used are available from Github: https://github.com/nataliering/Resolving-the-complex-Bordetella-pertussis-genome-using-barcoded-nanopore-sequencingIMPACT STATEMENTOver the past two decades, whole genome sequencing has allowed us to understand microbial pathogenicity and evolution on an unprecedented level. However, repetitive regions, like those found throughout the B. pertussis genome, have confounded our ability to resolve complex genomes using short-read sequencing technologies alone. To produce closed B. pertussis genome sequences it is necessary to use a sequencing technology which can generate reads longer than these problematic genomic regions. Using barcoded nanopore sequencing, we show that multiple B. pertussis genomes can be resolved per flow cell. Use of our assembly pipeline to resolve further B. pertussis genomes will advance understanding of how genome-level differences affect the phenotypes of strains which appear monomorphic at nucleotide-level.This work expands the recently emergent theme that even the most complex genomes can be resolved with sufficiently long sequencing reads. Additionally, we utilise a more widely accessible alternative sequencing platform to the Pacific Biosciences platform already used by large research centres such as the CDC. Our optimisation process, moreover, shows that the analysis tools favoured by the sequencing community do not necessarily produce the most accurate assemblies for all organisms; pipeline optimisation may therefore be beneficial in studies of unusually complex genomes.

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Systematic analysis of dark and camouflaged genes: disease-relevant genes hiding in plain sight

10.1101/514497 ◽

2019 ◽

Cited By ~ 1

Author(s):

Mark T. W. Ebbert ◽

Tanner D. Jensen ◽

Karen Jansen-West ◽

Jonathon P. Sens ◽

Joseph S. Reddy ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Sequencing Data ◽

Systematic Analysis ◽

Protein Coding ◽

Short Read ◽

Sequencing Project ◽

Short Read Sequencing ◽

Sequencing Technologies ◽

Long Read

AbstractBackgroundThe human genome contains ‘dark’ gene regions that cannot be adequately assembled or aligned using standard short-read sequencing technologies, preventing researchers from identifying mutations within these gene regions that may be relevant to human disease. Here, we identify regions that are ‘dark by depth’ (few mappable reads) and others that are ‘camouflaged’ (ambiguous alignment), and we assess how well long-read technologies resolve these regions. We further present an algorithm to resolve most camouflaged regions (including in short-read data) and apply it to the Alzheimer’s Disease Sequencing Project (ADSP; 13142 samples), as a proof of principle.ResultsBased on standard whole-genome lllumina sequencing data, we identified 37873 dark regions in 5857 gene bodies (3635 protein-coding) from pathways important to human health, development, and reproduction. Of the 5857 gene bodies, 494 (8.4%) were 100% dark (142 protein-coding) and 2046 (34.9%) were ≥5% dark (628 protein-coding). Exactly 2757 dark regions were in protein-coding exons (CDS) across 744 genes. Long-read sequencing technologies from 10x Genomics, PacBio, and Oxford Nanopore Technologies reduced dark CDS regions to approximately 45.1%, 33.3%, and 18.2% respectively. Applying our algorithm to the ADSP, we rescued 4622 exonic variants from 501 camouflaged genes, including a rare, ten-nucleotide frameshift deletion in CR1, a top Alzheimer’s disease gene, found in only five ADSP cases and zero controls.ConclusionsWhile we could not formally assess the CR1 frameshift mutation in Alzheimer’s disease (insufficient sample-size), we believe it merits investigating in a larger cohort. There remain thousands of potentially important genomic regions overlooked by short-read sequencing that are largely resolved by long-read technologies.

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High conservation combined with high plasticity: genomics and evolution of Borrelia bavariensis

10.21203/rs.3.rs-29892/v1 ◽

2020 ◽

Author(s):

Noémie S Becker ◽

Robert Ethan Rollins ◽

Kateryna Nosenko ◽

Alexander Paulus ◽

Samantha Martin ◽

...

Keyword(s):

Lyme Borreliosis ◽

Next Generation Sequencing Data ◽

Borrelia Burgdorferi Sensu Lato ◽

High Plasticity ◽

Sequencing Data ◽

Short Read ◽

Genome Reconstruction ◽

A Genome ◽

Long Read ◽

Genomic Studies

Abstract BackgroundBorrelia bavariensis is one of the agents of Lyme Borreliosis (or Lyme disease) in Eurasia. The genome of the Borrelia burgdorferi sensu lato species complex, that includes B. bavariensis , is known to be very complex and fragmented making the assembly of whole genomes with next-generation sequencing data a challenge. ResultsWe present a genome reconstruction for 33 B. bavariensis isolates from Eurasia based on long-read (Pacific Bioscience, for three isolates) and short-read (Illumina) data. We show that the combination of both sequencing techniques allows proper genome reconstruction of all plasmids in most cases but us e of a very close reference is necessary when only short-read sequencing data is available. B. bavariensis genomes combine a high degree of genetic conservation with high plasticity: all isolates share the main chromosome and five plasmids, but the repertoire of other plasmids is highly variable. In addition to plasmid losses and gains through horizontal transfer, we also observe several fusions between plasmids. Although European isolates of B. bavariensis have little diversity in genome content, there is some geographic structure to this variation. In contrast, each Asian isolate has a unique plasmid repertoire and we observe no geographically based differences between Japanese and Russian isolates. Comparing the genomes of Asian and European populations of B. bavariensis suggest s that some genes which are markedly different between the two populations may be good candidates for adaptation to the tick vector, ( Ixodes ricinus in Europe and I. persulcatus in Asia) . ConclusionsWe present the characterization of genomes of a large sample of B. bavariensis isolates and show that their plasmid content is highly variable. This study opens the way for genomic studies seeking to understand host and vector adaptation as well as human pathogenicity in Eurasian Lyme borreliosis agents.

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NextSV: a meta-caller for structural variants from low-coverage long-read sequencing data

10.1101/092544 ◽

2016 ◽

Author(s):

Li Fang ◽

Jiang Hu ◽

Depeng Wang ◽

Kai Wang

Keyword(s):

Whole Genome ◽

Ashkenazi Jewish ◽

Structural Variants ◽

Sequencing Data ◽

Short Read ◽

Short Read Sequencing ◽

Human Genomes ◽

Long Read ◽

Personal Genomes ◽

Low Coverage

AbstractBackgroundStructural variants (SVs) in human genomes are implicated in a variety of human diseases. Long-read sequencing delivers much longer read lengths than short-read sequencing and may greatly improve SV detection. However, due to the relatively high cost of long-read sequencing, it is unclear what coverage is needed and how to optimally use the aligners and SV callers.ResultsIn this study, we developed NextSV, a meta-caller to perform SV calling from low coverage long-read sequencing data. NextSV integrates three aligners and three SV callers and generates two integrated call sets (sensitive/stringent) for different analysis purposes. We evaluated SV calling performance of NextSV under different PacBio coverages on two personal genomes, NA12878 and HX1. Our results showed that, compared with running any single SV caller, NextSV stringent call set had higher precision and balanced accuracy (F1 score) while NextSV sensitive call set had a higher recall. At 10X coverage, the recall of NextSV sensitive call set was 93.5% to 94.1% for deletions and 87.9% to 93.2% for insertions, indicating that ~10X coverage might be an optimal coverage to use in practice, considering the balance between the sequencing costs and the recall rates. We further evaluated the Mendelian errors on an Ashkenazi Jewish trio dataset.ConclusionsOur results provide useful guidelines for SV detection from low coverage whole-genome PacBio data and we expect that NextSV will facilitate the analysis of SVs on long-read sequencing data.

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