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 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 Rapid, Paralog-Sensitive CNV Analysis of 2457 Human Genomes Using QuicK-mer2

Genes ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 141 ◽  
Author(s):  
Feichen Shen ◽  
Jeffrey M. Kidd
Keyword(s):  
Copy Number Variation ◽  
Copy Number ◽  
Sequence Data ◽  
Data Sets ◽  
Short Read ◽  
Major Mechanism ◽  
Rapid Construction ◽  
A Genome ◽  
Number Variation ◽  
Short Read Sequence

Gene duplication is a major mechanism for the evolution of gene novelty, and copy-number variation makes a major contribution to inter-individual genetic diversity. However, most approaches for studying copy-number variation rely upon uniquely mapping reads to a genome reference and are unable to distinguish among duplicated sequences. Specialized approaches to interrogate specific paralogs are comparatively slow and have a high degree of computational complexity, limiting their effective application to emerging population-scale data sets. We present QuicK-mer2, a self-contained, mapping-free approach that enables the rapid construction of paralog-specific copy-number maps from short-read sequence data. This approach is based on the tabulation of unique k-mer sequences from short-read data sets, and is able to analyze a 20X coverage human genome in approximately 20 min. We applied our approach to newly released sequence data from the 1000 Genomes Project, constructed paralog-specific copy-number maps from 2457 unrelated individuals, and uncovered copy-number variation of paralogous genes. We identify nine genes where none of the analyzed samples have a copy number of two, 92 genes where the majority of samples have a copy number other than two, and describe rare copy number variation effecting multiple genes at the APOBEC3 locus.

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

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.

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

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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