scholarly journals TETyper: a bioinformatic pipeline for classifying variation and genetic contexts of transposable elements from short-read whole-genome sequencing data

2018 ◽  
Vol 4 (12) ◽  
Author(s):  
Anna E. Sheppard ◽  
Nicole Stoesser ◽  
Ian German-Mesner ◽  
Kasi Vegesana ◽  
A. Sarah Walker ◽  
...  
Keyword(s):  
Transposable Elements ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Bioinformatic Pipeline ◽  
Short Read

scholarly journals TETyper: a bioinformatic pipeline for classifying variation and genetic contexts of transposable elements from short-read whole-genome sequencing data

2018 ◽  
Author(s):  
Anna E Sheppard ◽  
Nicole Stoesser ◽  
Ian German-Mesner ◽  
Kasi Vegesana ◽  
A Sarah Walker ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Transposable Elements ◽  
Genome Sequencing ◽  
Resistance Genes ◽  
Whole Genome Sequencing Data ◽  
Sequence Variants ◽  
Whole Genome ◽  
Sequencing Data ◽  
Bioinformatic Pipeline ◽  
Short Read

ABSTRACTMuch of the worldwide dissemination of antibiotic resistance has been driven by resistance gene associations with mobile genetic elements (MGEs), such as plasmids and transposons. Although increasing, our understanding of resistance spread remains relatively limited, as methods for tracking mobile resistance genes through multiple species, strains and plasmids are lacking. We have developed a bioinformatic pipeline for tracking variation within, and mobility of, specific transposable elements (TEs), such as transposons carrying antibiotic resistance genes. TETyper takes short-read whole-genome sequencing data as input and identifies single-nucleotide mutations and deletions within the TE of interest, to enable tracking of specific sequence variants, as well as the surrounding genetic context(s), to enable identification of transposition events. To investigate global dissemination of Klebsiella pneumoniae carbapenemase (KPC) and its associated transposon Tn4401, we applied TETyper to a collection of >3000 publicly available Illumina datasets containing blaKPC. This revealed surprising diversity, with >200 distinct flanking genetic contexts for Tn4401, indicating high levels of transposition. Integration of sample metadata revealed insights into associations between geographic locations, host species, Tn4401 sequence variants and flanking genetic contexts. To demonstrate the ability of TETyper to cope with high copy number TEs and to track specific short-term evolutionary changes, we also applied it to the insertion sequence IS26 within a defined K. pneumoniae outbreak. TETyper is implemented in python and is freely available at https://github.com/aesheppard/TETyper.

scholarly journals Rapid Diagnosis of Spinocerebellar Ataxia 36 in a Three‐Generation Family Using Short‐Read Whole‐Genome Sequencing Data

2020 ◽  
Vol 35 (9) ◽  
pp. 1675-1679
Author(s):  
Haloom Rafehi ◽  
David J. Szmulewicz ◽  
Kate Pope ◽  
Mathew Wallis ◽  
John Christodoulou ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Spinocerebellar Ataxia ◽  
Genome Sequencing ◽  
Rapid Diagnosis ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Short Read ◽  
Generation Family

scholarly journals Short-Read Whole-Genome Sequencing for Laboratory-Based Surveillance of Bordetella pertussis

2017 ◽  
Vol 55 (5) ◽  
pp. 1446-1453 ◽  
Author(s):  
Alex Marchand-Austin ◽  
Raymond S. W. Tsang ◽  
Jennifer L. Guthrie ◽  
Jennifer H. Ma ◽  
Gillian H. Lim ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Bordetella Pertussis ◽  
Vaccine Effectiveness ◽  
Vaccine Antigen ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Short Read ◽  
Content Type

ABSTRACTBordetella pertussisis a Gram-negative bacterium that causes respiratory infections in humans. Ongoing molecular surveillance ofB. pertussisacellular vaccine (aP) antigens is critical for understanding the interaction between evolutionary pressures, disease pathogenesis, and vaccine effectiveness. Methods currently used to characterize aP components are relatively labor-intensive and low throughput. To address this challenge, we sought to derive aP antigen genotypes from minimally processed short-read whole-genome sequencing data generated from 40 clinicalB. pertussisisolates and analyzed using the SRST2 bioinformatic package. SRST2 was able to identify aP antigen genotypes for all antigens with the exception of pertactin, possibly due to low read coverage in GC-rich low-complexity regions of variation. Two main genotypes were observed in addition to a singular third genotype that contained an 84-bp deletion that was identified by SRST2 despite the issues in allele calling. This method has the potential to generate large pools ofB. pertussismolecular data that can be linked to clinical and epidemiological information to facilitate research of vaccine effectiveness and disease severity in the context of emerging vaccine antigen-deficient strains.

scholarly journals Genome-Wide Identification of Microsatellites and Transposable Elements in the Dromedary Camel Genome Using Whole-Genome Sequencing Data

2019 ◽  
Vol 10 ◽  
Author(s):  
Reza Khalkhali-Evrigh ◽  
Nemat Hedayat-Evrigh ◽  
Seyed Hasan Hafezian ◽  
Ayoub Farhadi ◽  
Mohammad Reza Bakhtiarizadeh
Keyword(s):  
Transposable Elements ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome Sequencing Data ◽  
Dromedary Camel ◽  
Whole Genome ◽  
Sequencing Data ◽  
Genome Wide

scholarly journals Determining Streptococcus suis serotype from short-read whole-genome sequencing data

2016 ◽  
Vol 16 (1) ◽  
Author(s):  
Taryn B. T. Athey ◽  
Sarah Teatero ◽  
Sonia Lacouture ◽  
Daisuke Takamatsu ◽  
Marcelo Gottschalk ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Streptococcus Suis ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Short Read ◽  
Suis Serotype

scholarly journals Deriving Group A Streptococcus Typing Information from Short-Read Whole-Genome Sequencing Data

2014 ◽  
Vol 52 (6) ◽  
pp. 1871-1876 ◽  
Author(s):  
T. B. T. Athey ◽  
S. Teatero ◽  
A. Li ◽  
A. Marchand-Austin ◽  
B. W. Beall ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Group A Streptococcus ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Short Read ◽  
Group A
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