scholarly journals eXNVerify: coverage analysis for long and short-read sequencing data in clinical context

2021 ◽  
Author(s):  
Sebastian Porebski ◽  
Tomasz Stokowy
Keyword(s):  
Medical Diagnostics ◽  
Sequencing Data ◽  
Standard Samples ◽  
Accurate Identification ◽  
Short Read Sequencing ◽  
Pathogenic Variants ◽  
Coverage Analysis ◽  
Long Read ◽  
Experimental Technology

Accurate identification of genetic variants to a large extent is based on type of experimental technology, quality of the material and coverage of obtained sequencing data. Our motivation was to create a tool that will evaluate genome coverage and accelerate the introduction of long-read sequencing to medical diagnostics and clinical practice. Here we present eXNVerify: a tool for inspection of clinical data in the context of pathogenic variants. The tool calculates Clinical Depth Coverage – a measure of coverage which we introduce to evaluate loci with pathogenic germline and somatic variants reported in ClinVar. The tool additionally provides visualization options for user-defined genes of interest. Finally, we present an examples of BRCA1, TP53, CFTR application and results of a test conducted in the Extensive Sequence Dataset of Gold-Standard Samples for Benchmarking and Development.

scholarly journals Rapid Mycobacterium tuberculosis spoligotyping from uncorrected long reads using Galru

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.

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

2019 ◽  
Vol 8 (34) ◽  
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.

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

2018 ◽  
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.

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

2019 ◽  
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.

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

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.

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

2019 ◽  
Vol 10 (1) ◽  
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 detection and breakpoint identification for structural variants (SVs). Here 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 demonstrate 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.

scholarly journals Complete Genome Sequence of Vibrio rotiferianus Strain AM7

2020 ◽  
Vol 9 (21) ◽  
Author(s):  
Kentaro Miyazaki ◽  
Apirak Wiseschart ◽  
Kusol Pootanakit ◽  
Kei Kitahara
Keyword(s):  
Genome Sequence ◽  
Complete Genome Sequence ◽  
Complete Genome ◽  
The Novel ◽  
Sequencing Data ◽  
Short Read ◽  
Content Type ◽  
Short Read Sequencing ◽  
Oxford Nanopore ◽  
Long Read

ABSTRACT We isolated the novel strain Vibrio rotiferianus AM7 from the shell of an abalone. In this article, we report the complete genome sequence of this organism, which was obtained by combining Oxford Nanopore long-read and Illumina short-read sequencing data.

scholarly journals Complete Genome Sequence of Staphylococcus arlettae Strain P2, Isolated from a Laboratory Environment

2019 ◽  
Vol 8 (45) ◽  
Author(s):  
Hiroki Yu ◽  
Makoto Taniguchi ◽  
Kazuma Uesaka ◽  
Apirak Wiseschart ◽  
Kusol Pootanakit ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Complete Genome Sequence ◽  
Complete Genome ◽  
Hybrid Approach ◽  
Illumina Miseq ◽  
Sequencing Data ◽  
Content Type ◽  
Short Read Sequencing ◽  
Oxford Nanopore ◽  
Long Read

Staphylococcus arlettae is one coagulase-negative species in the bacterial genus Staphylococcus. Here, we describe the closed complete genome sequence of S. arlettae strain P2, which was obtained using a hybrid approach combining Oxford Nanopore long-read and Illumina MiSeq short-read sequencing data.

scholarly journals SMRT-Cappable-seq reveals complex operon variants in bacteria

2018 ◽  
Author(s):  
Bo Yan ◽  
Matthew Boitano ◽  
Tyson Clark ◽  
Laurence Ettwiller
Keyword(s):  
Single Molecule ◽  
Gene Network ◽  
Accurate Identification ◽  
E Coli ◽  
Short Read Sequencing ◽  
Genome Wide ◽  
Long Read ◽  
Definition Of ◽  
Bacterial Genes

AbstractCurrent methods for genome-wide analysis of gene expression requires shredding original transcripts into small fragments for short-read sequencing. In bacteria, the resulting fragmented information hides operon complexity. Additionally,in-vivoprocessing of transcripts confounds the accurate identification of the 5’ and 3’ ends of operons. Here we developed a novel methodology called SMRT-Cappable-seq that combines the isolation of unfragmented primary transcripts with single-molecule long read sequencing. Applied toE. coli, this technology results in an unprecedented definition of the transcriptome with 34% of the known operons being extended by at least one gene. Furthermore, 40% of transcription termination sites have read-through that alters the gene content of the operons. As a result, most of the bacterial genes are present in multiple operon variants reminiscent of eukaryotic splicing. By providing an unprecedented granularity in the operon structure, this study represents an important resource for the study of prokaryotic gene network and regulation.

scholarly journals Phased Haplotype Resolution of the SLC6A4 Promoter Using Long-Read Single Molecule Real-Time (SMRT) Sequencing

Genes ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1333
Author(s):  
Mariana R. Botton ◽  
Yao Yang ◽  
Erick R. Scott ◽  
Robert J. Desnick ◽  
Stuart A. Scott
Keyword(s):  
Real Time ◽  
Single Molecule ◽  
Variable Number ◽  
Sequencing Data ◽  
Smrt Sequencing ◽  
Short Read ◽  
Short Read Sequencing ◽  
Sequencing Method ◽  
Long Read ◽  
S Allele

The SLC6A4 gene has been implicated in psychiatric disorder susceptibility and antidepressant response variability. The SLC6A4 promoter is defined by a variable number of homologous 20–24 bp repeats (5-HTTLPR), and long (L) and short (S) alleles are associated with higher and lower expression, respectively. However, this insertion/deletion variant is most informative when considered as a haplotype with the rs25531 and rs25532 variants. Therefore, we developed a long-read single molecule real-time (SMRT) sequencing method to interrogate the SLC6A4 promoter region. A total of 120 samples were subjected to SLC6A4 long-read SMRT sequencing, primarily selected based on available short-read sequencing data. Short-read genome sequencing from the 1000 Genomes (1KG) Project (~5X) and the Genetic Testing Reference Material Coordination Program (~45X), as well as high-depth short-read capture-based sequencing (~330X), could not identify the 5-HTTLPR short (S) allele, nor could short-read sequencing phase any identified variants. In contrast, long-read SMRT sequencing unambiguously identified the 5-HTTLPR short (S) allele (frequency of 0.467) and phased SLC6A4 promoter haplotypes. Additionally, discordant rs25531 genotypes were reviewed and determined to be short-read errors. Taken together, long-read SMRT sequencing is an innovative and robust method for phased resolution of the SLC6A4 promoter, which could enable more accurate pharmacogenetic testing for both research and clinical applications.

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