scholarly journals Finished bacterial genomes from shotgun sequence data

2012 ◽  
Vol 22 (11) ◽  
pp. 2270-2277 ◽  
Author(s):  
F. J. Ribeiro ◽  
D. Przybylski ◽  
S. Yin ◽  
T. Sharpe ◽  
S. Gnerre ◽  
...  
Keyword(s):  
Sequence Data ◽  
Bacterial Genomes ◽  
Shotgun Sequence

scholarly journals Two hundred and fifty-four metagenome-assembled bacterial genomes from the bank vole gut microbiota

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Anton Lavrinienko ◽  
Eugene Tukalenko ◽  
Timothy A. Mousseau ◽  
Luke R. Thompson ◽  
Rob Knight ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Community Composition ◽  
Small Mammal ◽  
Bank Vole ◽  
Sequence Data ◽  
Myodes Glareolus ◽  
Wild Rodents ◽  
Bacterial Genomes ◽  
Shotgun Sequence ◽  
Essential Services

Abstract Vertebrate gut microbiota provide many essential services to their host. To better understand the diversity of such services provided by gut microbiota in wild rodents, we assembled metagenome shotgun sequence data from a small mammal, the bank vole Myodes glareolus (Rodentia, Cricetidae). We were able to identify 254 metagenome assembled genomes (MAGs) that were at least 50% (n = 133 MAGs), 80% (n = 77 MAGs) or 95% (n = 44 MAGs) complete. As typical for a rodent gut microbiota, these MAGs are dominated by taxa assigned to the phyla Bacteroidetes (n = 132 MAGs) and Firmicutes (n = 80), with some Spirochaetes (n = 15) and Proteobacteria (n = 11). Based on coverage over contigs, Bacteroidetes were estimated to be most abundant group, followed by Firmicutes, Spirochaetes and Proteobacteria. These draft bacterial genomes can be used freely to determine the likely functions of gut microbiota community composition in wild rodents.

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 Extensive Pericentric Rearrangements in the Bread Wheat ( Triticum aestivum L.) Genotype “Chinese Spring” Revealed from Chromosome Shotgun Sequence Data

2014 ◽  
Vol 6 (11) ◽  
pp. 3039-3048 ◽  
Author(s):  
Jian Ma ◽  
Jiri Stiller ◽  
Yuming Wei ◽  
You-Liang Zheng ◽  
Katrien M. Devos ◽  
...  
Keyword(s):  
Triticum Aestivum ◽  
Bread Wheat ◽  
Chinese Spring ◽  
Sequence Data ◽  
Triticum Aestivum L ◽  
Shotgun Sequence

scholarly journals Long-read, whole-genome shotgun sequence data for five model organisms

2014 ◽  
Vol 1 (1) ◽  
Author(s):  
Kristi E Kim ◽  
Paul Peluso ◽  
Primo Babayan ◽  
P. Jane Yeadon ◽  
Charles Yu ◽  
...  
Keyword(s):  
Sequence Data ◽  
Whole Genome Shotgun ◽  
Model Organisms ◽  
Whole Genome ◽  
Shotgun Sequence ◽  
Whole Genome Shotgun Sequence ◽  
Long Read ◽  
Genome Shotgun 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.

scholarly journals Mapping Microbiome Signatures Associated With Antibiotic Usage On A Swine Production Farm Using Amplicon And Shotgun Data

2021 ◽  
Author(s):  
Adrian Muwonge ◽  
Jolinda Pollock ◽  
Shih Barbara ◽  
Michael R. Hutchings ◽  
Mark Bronsvoort ◽  
...  
Keyword(s):  
Sequence Data ◽  
Antibiotic Use ◽  
Efflux Pumps ◽  
Treated Group ◽  
Antibiotic Usage ◽  
Growing Pigs ◽  
Metagenomic Data ◽  
Rrna Gene ◽  
Swine Production ◽  
Shotgun Sequence

Abstract Background: High antimicrobial usage in swine production has the potential to create reservoirs of antimicrobial resistance (AMR) genes which are transferable to human pathogens via mobile genetic elements. Understanding microbial community responses to antibiotic use is central to unravelling transfer of such resistance genes. Our previous investigation revealed a scenario of optimal antibiotic activity associated with saturation of AMR genes on this farm. Here, we use amplicon and shotgun sequence data to investigate the microbiome signatures that underwrite such a phenomenon.Results: We generated 1.24 and 576 million high quality 16S rRNA gene amplicon and shotgun sequences from 24 porcine faecal samples, respectively. The ratio of taxa detection at genus level between the two methods was 1:24. Using shotgun sequence data, 235 unique AMR genes, 122 modes of action and 17 antibiotic classes were identified using the MEGARes AMR database. Antibiotic usage in growing pigs was significantly associated with microbial and AMR resistome structural and compositional changes detectable two weeks after antibiotic initiation. These were characterised by a down regulation of MDR efflux pumps and an up regulation of macrolide-specific efflux pumps in the growing pigs (treated-group) linked to lower abundance of Verrucomicrobiaeceae. In the sows (non-treated group), a potentially undetected infection, was characterised by a high abundance of pathogenic viral sequences, microbial structural changes i.e. family Alcaligenaceae, and an up regulation of beta-lactamases, including MDR efflux pumps. We assembled 682 near complete bacterial genomes revealing that a large proportion of the resistome is carried by Firmicutes and Proteobacteria, specifically multi-class gene carriage by Clostridium species and Escherichia coli, which occurred exclusively in the treatment group.Conclusion: Microbiome signatures i.e. microbial structure, composition and resistome carriage associated with antibiotic-use can be cost effectively screened with amplicon sequencing but their granularity unravelled using shotgun metagenomic data.

scholarly journals MOST: a modified MLST typing tool based on short read sequencing

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2308 ◽  
Author(s):  
Rediat Tewolde ◽  
Timothy Dallman ◽  
Ulf Schaefer ◽  
Carmen L. Sheppard ◽  
Philip Ashton ◽  
...  
Keyword(s):  
Conventional Method ◽  
Sequence Data ◽  
Pcr Amplification ◽  
Housekeeping Genes ◽  
Data Sets ◽  
Bacterial Genomes ◽  
Bacterial Populations ◽  
Short Read ◽  
Short Read Sequence ◽  
Low Coverage

Multilocus sequence typing (MLST) is an effective method to describe bacterial populations. Conventionally, MLST involves Polymerase Chain Reaction (PCR) amplification of housekeeping genes followed by Sanger DNA sequencing. Public Health England (PHE) is in the process of replacing the conventional MLST methodology with a method based on short read sequence data derived from Whole Genome Sequencing (WGS). This paper reports the comparison of the reliability of MLST results derived from WGS data, comparing mapping and assembly-based approaches to conventional methods using 323 bacterial genomes of diverse species. The sensitivity of the two WGS based methods were further investigated with 26 mixed and 29 low coverage genomic data sets fromSalmonella enteridisandStreptococcus pneumoniae. Of the 323 samples, 92.9% (n= 300), 97.5% (n= 315) and 99.7% (n= 322) full MLST profiles were derived by the conventional method, assembly- and mapping-based approaches, respectively. The concordance between samples that were typed by conventional (92.9%) and both WGS methods was 100%. From the 55 mixed and low coverage genomes, 89.1% (n= 49) and 67.3% (n= 37) full MLST profiles were derived from the mapping and assembly based approaches, respectively. In conclusion, deriving MLST from WGS data is more sensitive than the conventional method. When comparing WGS based methods, the mapping based approach was the most sensitive. In addition, the mapping based approach described here derives quality metrics, which are difficult to determine quantitatively using conventional and WGS-assembly based approaches.

scholarly journals Organization and Evolution of Primate Centromeric DNA from Whole-Genome Shotgun Sequence Data

2007 ◽  
Vol 3 (9) ◽  
pp. e181 ◽  
Author(s):  
Can Alkan ◽  
Mario Ventura ◽  
Nicoletta Archidiacono ◽  
Mariano Rocchi ◽  
S. Cenk Sahinalp ◽  
...  
Keyword(s):  
Sequence Data ◽  
Whole Genome Shotgun ◽  
Whole Genome ◽  
Centromeric Dna ◽  
Shotgun Sequence ◽  
Whole Genome Shotgun Sequence ◽  
Genome Shotgun Sequence
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