scholarly journals EcOH: In silico serotyping of E. coli from short read data

2015 ◽  
Author(s):  
Danielle Ingle ◽  
Mary Valcanis ◽  
Alex Kuzevski ◽  
Marija Tauschek ◽  
Michael Inouye ◽  
...  
Keyword(s):  
In Silico ◽  
Genetic Basis ◽  
De Novo ◽  
Sequence Data ◽  
Bacterial Isolates ◽  
De Novo Genome Assembly ◽  
Short Read ◽  
The Public ◽  
E Coli ◽  
Short Read Sequence

The lipopolysaccharide (O) and flagellar (H) surface antigens of Escherichia coli are targets for serotyping that have traditionally been used to identify pathogenic lineages of E. coli. As serotyping has several limitations, public health reference laboratories are increasingly moving towards whole genome sequencing (WGS) for the rapid characterisation of bacterial isolates. Here we present a method to rapidly and accurately serotype E. coli isolates from raw, short read sequence data, leveraging the known genetic basis for the biosynthesis of O- and H-antigens. Our approach bypasses the need for de novo genome assembly by directly screening WGS reads against a curated database of alleles linked to known E. coli O-groups and H-types (the EcOH database) using the software package SRST2. We validated our approach by comparing in silico results with those obtained via serological phenotyping of 197 enteropathogenic (EPEC) isolates. We also demonstrated the utility of our method to characterise enterotoxigenic E. coli (ETEC) and the uropathogenic E. coli (UPEC) epidemic clone ST131, and for in silico serotyping of foodborne outbreak-related isolates in the public GenomeTrakr database.

scholarly journals De novo assembly using low-coverage short read sequence data from the rice pathogen Pseudomonas syringae pv. oryzae

2008 ◽  
Vol 19 (2) ◽  
pp. 294-305 ◽  
Author(s):  
J. A. Reinhardt ◽  
D. A. Baltrus ◽  
M. T. Nishimura ◽  
W. R. Jeck ◽  
C. D. Jones ◽  
...  
Keyword(s):  
Pseudomonas Syringae ◽  
De Novo Assembly ◽  
De Novo ◽  
Sequence Data ◽  
Short Read ◽  
Short Read Sequence ◽  
Low Coverage

scholarly journals Easy and Accurate Reconstruction of Whole HIV Genomes from Short-Read Sequence Data

2016 ◽  
Author(s):  
Chris Wymant ◽  
François Blanquart ◽  
Astrid Gall ◽  
Margreet Bakker ◽  
Daniela Bezemer ◽  
...  
Keyword(s):  
De Novo ◽  
Sequence Data ◽  
Consensus Sequence ◽  
Heterogeneous Data ◽  
Reference Sequence ◽  
Data Sets ◽  
Illumina Platform ◽  
Short Read ◽  
Variant Information ◽  
Short Read Sequence

AbstractNext-generation sequencing has yet to be widely adopted for HIV. The difficulty of accurately reconstructing the consensus sequence of a quasispecies from reads (short fragments of DNA) in the presence of rapid between- and within-host evolution may have presented a barrier. In particular, mapping (aligning) reads to a reference sequence leads to biased loss of information; this bias can distort epidemiological and evolutionary conclusions.De novoassembly avoids this bias by effectively aligning the reads to themselves, producing a set of sequences called contigs. However contigs provide only a partial summary of the reads, misassembly may result in their having an incorrect structure, and no information is available at parts of the genome where contigs could not be assembled. To address these problems we developed the toolshiverto preprocess reads for quality and contamination, then map them to a reference tailored to the sample using corrected contigs supplemented with existing reference sequences. Run with two commands per sample, it can easily be used for large heterogeneous data sets. We useshiverto reconstruct the consensus sequence and minority variant information from paired-end short-read data produced with the Illumina platform, for 65 existing publicly available samples and 50 new samples. We show the systematic superiority of mapping toshiver’s constructed reference over mapping the same reads to the standard reference HXB2: an average of 29 bases per sample are called differently, of which 98.5% are supported by higher coverage. We also provide a practical guide to working with imperfect contigs.

scholarly journals Genome sequences reveal global dispersal routes and suggest convergent genetic adaptations in seahorse evolution

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Chunyan Li ◽  
Melisa Olave ◽  
Yali Hou ◽  
Geng Qin ◽  
Ralf F. Schneider ◽  
...  
Keyword(s):  
Coastal Waters ◽  
Genetic Basis ◽  
De Novo ◽  
Ocean Currents ◽  
Rapid Adaptation ◽  
Developmental Gene ◽  
De Novo Genome Assembly ◽  
Biogeographic Patterns ◽  
Hippocampus Erectus ◽  
New Habitats

AbstractSeahorses have a circum-global distribution in tropical to temperate coastal waters. Yet, seahorses show many adaptations for a sedentary, cryptic lifestyle: they require specific habitats, such as seagrass, kelp or coral reefs, lack pelvic and caudal fins, and give birth to directly developed offspring without pronounced pelagic larval stage, rendering long-range dispersal by conventional means inefficient. Here we investigate seahorses’ worldwide dispersal and biogeographic patterns based on a de novo genome assembly of Hippocampus erectus as well as 358 re-sequenced genomes from 21 species. Seahorses evolved in the late Oligocene and subsequent circum-global colonization routes are identified and linked to changing dynamics in ocean currents and paleo-temporal seaway openings. Furthermore, the genetic basis of the recurring “bony spines” adaptive phenotype is linked to independent substitutions in a key developmental gene. Analyses thus suggest that rafting via ocean currents compensates for poor dispersal and rapid adaptation facilitates colonizing new habitats.

scholarly journals Accurate long-read de novo assembly evaluation with Inspector

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yu Chen ◽  
Yixin Zhang ◽  
Amy Y. Wang ◽  
Min Gao ◽  
Zechen Chong
Keyword(s):  
Genome Assembly ◽  
De Novo Assembly ◽  
In Silico ◽  
Large Scale ◽  
De Novo ◽  
Small Scale ◽  
De Novo Genome Assembly ◽  
Consensus Sequences ◽  
Assembly Evaluation ◽  
Long Read

AbstractLong-read de novo genome assembly continues to advance rapidly. However, there is a lack of effective tools to accurately evaluate the assembly results, especially for structural errors. We present Inspector, a reference-free long-read de novo assembly evaluator which faithfully reports types of errors and their precise locations. Notably, Inspector can correct the assembly errors based on consensus sequences derived from raw reads covering erroneous regions. Based on in silico and long-read assembly results from multiple long-read data and assemblers, we demonstrate that in addition to providing generic metrics, Inspector can accurately identify both large-scale and small-scale assembly errors.

scholarly journals The large-scale blast score ratio (LS-BSR) pipeline: a method to rapidly compare genetic content between bacterial genomes

2014 ◽  
Author(s):  
Jason W Sahl ◽  
Greg Caporaso ◽  
David A Rasko ◽  
Paul S Keim
Keyword(s):  
Large Scale ◽  
Sequence Data ◽  
Parallel Implementation ◽  
Genetic Relationships ◽  
Clinical Diagnostics ◽  
Whole Genome Sequence ◽  
Bacterial Isolates ◽  
Bacterial Genomes ◽  
E Coli ◽  
Blast Score

Background. As whole genome sequence data from bacterial isolates becomes cheaper to generate, computational methods are needed to correlate sequence data with biological observations. Here we present the large-scale BLAST score ratio (LS-BSR) pipeline, which rapidly compares the genetic content of hundreds to thousands of bacterial genomes, and returns a matrix that describes the relatedness of all coding sequences (CDSs) in all genomes surveyed. This matrix can be easily parsed in order to identify genetic relationships between bacterial genomes. Although pipelines have been published that group peptides by sequence similarity, no other software performs the large-scale, flexible, full-genome comparative analyses carried out by LS-BSR. Results. To demonstrate the utility of the method, the LS-BSR pipeline was tested on 96 Escherichia coli and Shigella genomes; the pipeline ran in 163 minutes using 16 processors, which is a greater than 7-fold speedup compared to using a single processor. The BSR values for each CDS, which indicate a relative level of relatedness, were then mapped to each genome on an independent core genome single nucleotide polymorphism (SNP) based phylogeny. Comparisons were then used to identify clade specific CDS markers and validate the LS-BSR pipeline based on molecular markers that delineate between classical E. coli pathogenic variant (pathovar) designations. Scalability tests demonstrated that the LS-BSR pipeline can process 1,000 E. coli genomes in ~60h using 16 processors. Conclusions. LS-BSR is an open-source, parallel implementation of the BSR algorithm, enabling rapid comparison of the genetic content of large numbers of genomes. The results of the pipeline can be used to identify specific markers between user-defined phylogenetic groups, and to identify the loss and/or acquisition of genetic information between bacterial isolates. Taxa-specific genetic markers can then be translated into clinical diagnostics, or can be used to identify broadly conserved putative therapeutic candidates.

scholarly journals Hybrid De Novo Genome Assembly Using MiSeq and SOLiD Short Read Data

PLoS ONE ◽  
2015 ◽  
Vol 10 (4) ◽  
pp. e0126289 ◽  
Author(s):  
Tsutomu Ikegami ◽  
Toyohiro Inatsugi ◽  
Isao Kojima ◽  
Myco Umemura ◽  
Hiroko Hagiwara ◽  
...  
Keyword(s):  
Genome Assembly ◽  
De Novo ◽  
De Novo Genome Assembly ◽  
Short Read

scholarly journals Choice of Reference Sequence and Assembler for Alignment of Listeria monocytogenes Short-Read Sequence Data Greatly Influences Rates of Error in SNP Analyses

PLoS ONE ◽  
2014 ◽  
Vol 9 (8) ◽  
pp. e104579 ◽  
Author(s):  
Arthur W. Pightling ◽  
Nicholas Petronella ◽  
Franco Pagotto
Keyword(s):  
Listeria Monocytogenes ◽  
Sequence Data ◽  
Reference Sequence ◽  
Short Read ◽  
Short Read Sequence

scholarly journals ISMapper: Identifying insertion sequences in bacterial genomes from short read sequence data

2015 ◽  
Author(s):  
Jane Hawkey ◽  
Mohammad Hamidian ◽  
Ryan R Wick ◽  
David J Edwards ◽  
Helen Billman-Jacobe ◽  
...  
Keyword(s):  
Sequence Data ◽  
Insertion Sequences ◽  
Bacterial Genomes ◽  
Short Read ◽  
Phenotypic Resistance ◽  
Genome Wide ◽  
Wide Range ◽  
Multiple Copies ◽  
Short Read Sequence ◽  
Insertion Sites

Background Insertion sequences (IS) are small transposable elements, commonly found in bacterial genomes. Identifying the location of IS in bacterial genomes can be useful for a variety of purposes including epidemiological tracking and predicting antibiotic resistance. However IS are commonly present in multiple copies in a single genome, which complicates genome assembly and the identification of IS insertion sites. Here we present ISMapper, a mapping-based tool for identification of the site and orientation of IS insertions in bacterial genomes, direct from paired-end short read data. Results ISMapper was validated using three types of short read data: (i) simulated reads from a variety of species, (ii) Illumina reads from 5 isolates for which finished genome sequences were available for comparison, and (iii) Illumina reads from 7 Acinetobacter baumannii isolates for which predicted IS locations were tested using PCR. A total of 20 genomes, including 13 species and 32 distinct IS, were used for validation. ISMapper correctly identified 96% of known IS insertions in the analysis of simulated reads, and 98% in real Illumina reads. Subsampling of real Illumina reads to lower depths indicated ISMapper was reliable for average genome-wide read depths >20x. All ISAba1 insertions identified by ISMapper in the A. baumannii genomes were confirmed by PCR. In each A. baumannii genome, ISMapper successfully identified an IS insertion upstream of the ampC beta-lactamase that could explain phenotypic resistance to third-generation cephalosporins. The utility of ISMapper was further demonstrated by profiling genome-wide IS6110 insertions in 138 publicly available Mycobacterium tuberculosis genomes, revealing lineage-specific insertions and multiple insertion hotspots. Conclusions ISMapper provides a rapid and robust method for identifying IS insertion sites direct from short read data, with a high degree of accuracy demonstrated across a wide range of bacteria.

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