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

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.

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MOST: A modified MLST typing tool based on short read sequencing

10.7287/peerj.preprints.1971v1 ◽

2016 ◽

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 325 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 from Salmonella enteridis and Streptococcus pneumoniae. Of the 325 samples, 92.9% (n=302), 97.2% (n=316) and 99.7% (n=324) 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, 90.9% (n=50) 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.

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

10.1101/032151 ◽

2015 ◽

Cited By ~ 2

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.

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

10.1101/092916 ◽

2016 ◽

Cited By ~ 4

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.

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MOST: A modified MLST typing tool based on short read sequencing

10.7287/peerj.preprints.1971 ◽

2016 ◽

Cited By ~ 1

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 325 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 from Salmonella enteridis and Streptococcus pneumoniae. Of the 325 samples, 92.9% (n=302), 97.2% (n=316) and 99.7% (n=324) 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, 90.9% (n=50) 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.

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Phylogenomic inferences from reference-mapped and de novo assembled short-read sequence data using RADseq sequencing of California white oaks (Quercus section Quercus)

Genome ◽

10.1139/gen-2016-0202 ◽

2017 ◽

Vol 60 (9) ◽

pp. 743-755 ◽

Cited By ~ 21

Author(s):

Sorel Fitz-Gibbon ◽

Andrew L. Hipp ◽

Kasey K. Pham ◽

Paul S. Manos ◽

Victoria L. Sork

Keyword(s):

De Novo Assembly ◽

Reference Genome ◽

De Novo ◽

Sequence Data ◽

Draft Genome ◽

Reduced Representation ◽

Advantages And Disadvantages ◽

Mapping Sequence ◽

Wide Range ◽

Short Read Sequence

The emergence of next generation sequencing has increased by several orders of magnitude the amount of data available for phylogenetics. Reduced representation approaches, such as restriction-sited associated DNA sequencing (RADseq), have proven useful for phylogenetic studies of non-model species at a wide range of phylogenetic depths. However, analysis of these datasets is not uniform and we know little about the potential benefits and drawbacks of de novo assembly versus assembly by mapping to a reference genome. Using RADseq data for 83 oak samples representing 16 taxa, we identified variants via three pipelines: mapping sequence reads to a recently published draft genome of Quercus lobata, and de novo assembly under two sets of locus filters. For each pipeline, we inferred the maximum likelihood phylogeny. All pipelines produced similar trees, with minor shifts in relationships within well-supported clades, despite the fact that they yielded different numbers of loci (68 000 – 111 000 loci) and different degrees of overlap with the reference genome. We conclude that both the reference-aligned and de novo assembly pipelines yield reliable results, and that advantages and disadvantages of these approaches pertain mainly to downstream uses of RADseq data, not to phylogenetic inference per se.

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Faculty Opinions recommendation of Efficient de novo assembly of single-cell bacterial genomes from short-read data sets.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.13296960.14657061 ◽

2011 ◽

Author(s):

Steven Salzberg

Keyword(s):

Single Cell ◽

De Novo Assembly ◽

De Novo ◽

Data Sets ◽

Bacterial Genomes ◽

Short Read

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A long reads-based de-novo assembly of the genome of the Arlee homozygous line reveals chromosomal rearrangements in rainbow trout

G3 Genes|Genome|Genetics ◽

10.1093/g3journal/jkab052 ◽

2021 ◽

Author(s):

Guangtu Gao ◽

Susana Magadan ◽

Geoffrey C Waldbieser ◽

Ramey C Youngblood ◽

Paul A Wheeler ◽

...

Keyword(s):

Rainbow Trout ◽

Chromosome Number ◽

Genome Assembly ◽

De Novo Assembly ◽

De Novo ◽

Sequence Data ◽

Structural Variations ◽

High Coverage ◽

Haploid Chromosome Number ◽

Long Reads

Abstract Currently, there is still a need to improve the contiguity of the rainbow trout reference genome and to use multiple genetic backgrounds that will represent the genetic diversity of this species. The Arlee doubled haploid line was originated from a domesticated hatchery strain that was originally collected from the northern California coast. The Canu pipeline was used to generate the Arlee line genome de-novo assembly from high coverage PacBio long-reads sequence data. The assembly was further improved with Bionano optical maps and Hi-C proximity ligation sequence data to generate 32 major scaffolds corresponding to the karyotype of the Arlee line (2 N = 64). It is composed of 938 scaffolds with N50 of 39.16 Mb and a total length of 2.33 Gb, of which ∼95% was in 32 chromosome sequences with only 438 gaps between contigs and scaffolds. In rainbow trout the haploid chromosome number can vary from 29 to 32. In the Arlee karyotype the haploid chromosome number is 32 because chromosomes Omy04, 14 and 25 are divided into six acrocentric chromosomes. Additional structural variations that were identified in the Arlee genome included the major inversions on chromosomes Omy05 and Omy20 and additional 15 smaller inversions that will require further validation. This is also the first rainbow trout genome assembly that includes a scaffold with the sex-determination gene (sdY) in the chromosome Y sequence. The utility of this genome assembly is demonstrated through the improved annotation of the duplicated genome loci that harbor the IGH genes on chromosomes Omy12 and Omy13.

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