Improving tuberculosis surveillance by detecting international transmission using publicly available whole-genome sequencing data

AbstractIntroductionImproving the surveillance of tuberculosis (TB) is especially important for multidrug-resistant (MDR) and extensively drug-resistant (XDR)-TB. The large amount of publicly available whole-genome sequencing (WGS) data for TB gives us the chance to re-use data and to perform additional analysis at a large scale.AimWe assessed the usefulness of raw WGS data of global MDR/XDR-TB isolates available from public repositories to improve TB surveillance.MethodsWe extracted raw WGS data and the related metadata of Mycobacterium tuberculosis isolates available from the Sequence Read Archive. We compared this public dataset with WGS data and metadata of 131 MDR- and XDR-TB isolates from Germany in 2012-2013.ResultsWe aggregated a dataset that includes 1,081 MDR and 250 XDR isolates among which we identified 133 molecular clusters. In 16 clusters, the isolates were from at least two different countries. For example, cluster2 included 56 MDR/XDR isolates from Moldova, Georgia, and Germany. By comparing the WGS data from Germany and the public dataset, we found that 11 clusters contained at least one isolate from Germany and at least one isolate from another country. We could, therefore, connect TB cases despite missing epidemiological information.ConclusionWe demonstrated the added value of using WGS raw data from public repositories to contribute to TB surveillance. By comparing the German and the public dataset, we identified potential international transmission events. Thus, using this approach might support the interpretation of national surveillance results in an international context.

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Improving tuberculosis surveillance by detecting international transmission using publicly available whole genome sequencing data

Eurosurveillance ◽

10.2807/1560-7917.es.2021.26.2.1900677 ◽

2021 ◽

Vol 26 (2) ◽

Author(s):

Andrea Sanchini ◽

Christine Jandrasits ◽

Julius Tembrockhaus ◽

Thomas Andreas Kohl ◽

Christian Utpatel ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Large Scale ◽

Added Value ◽

Whole Genome Sequencing Data ◽

Whole Genome ◽

International Transmission ◽

The Public ◽

Public Dataset ◽

Public Repositories

Introduction Improving the surveillance of tuberculosis (TB) is especially important for multidrug-resistant (MDR) and extensively drug-resistant (XDR) TB. The large amount of publicly available whole genome sequencing (WGS) data for TB gives us the chance to re-use data and to perform additional analyses at a large scale. Aim We assessed the usefulness of raw WGS data of global MDR/XDR Mycobacterium tuberculosis isolates available from public repositories to improve TB surveillance. Methods We extracted raw WGS data and the related metadata of M. tuberculosis isolates available from the Sequence Read Archive. We compared this public dataset with WGS data and metadata of 131 MDR- and XDR M. tuberculosis isolates from Germany in 2012 and 2013. Results We aggregated a dataset that included 1,081 MDR and 250 XDR isolates among which we identified 133 molecular clusters. In 16 clusters, the isolates were from at least two different countries. For example, Cluster 2 included 56 MDR/XDR isolates from Moldova, Georgia and Germany. When comparing the WGS data from Germany with the public dataset, we found that 11 clusters contained at least one isolate from Germany and at least one isolate from another country. We could, therefore, connect TB cases despite missing epidemiological information. Conclusion We demonstrated the added value of using WGS raw data from public repositories to contribute to TB surveillance. Comparing the German with the public dataset, we identified potential international transmission events. Thus, using this approach might support the interpretation of national surveillance results in an international context.

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Plasmids or no plasmids? A comparison between the agilent TapeStation and whole-genome sequencing data in a large-scale bacterial sequencing project

10.26226/morressier.56d5ba27d462b80296c95fe7 ◽

2016 ◽

Author(s):

Sarah Alexander

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Large Scale ◽

Whole Genome Sequencing Data ◽

Whole Genome ◽

Sequencing Data ◽

Sequencing Project

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SeqSero2: Rapid and Improved Salmonella Serotype Determination Using Whole-Genome Sequencing Data

Applied and Environmental Microbiology ◽

10.1128/aem.01746-19 ◽

2019 ◽

Vol 85 (23) ◽

Cited By ~ 25

Author(s):

Shaokang Zhang ◽

Hendrik C. den Bakker ◽

Shaoting Li ◽

Jessica Chen ◽

Blake A. Dinsmore ◽

...

Keyword(s):

Public Health ◽

United States ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Large Scale ◽

Draft Genome ◽

The United States ◽

Whole Genome Sequencing Data ◽

Whole Genome ◽

Link Type

ABSTRACT SeqSero, launched in 2015, is a software tool for Salmonella serotype determination from whole-genome sequencing (WGS) data. Despite its routine use in public health and food safety laboratories in the United States and other countries, the original SeqSero pipeline is relatively slow (minutes per genome using sequencing reads), is not optimized for draft genome assemblies, and may assign multiple serotypes for a strain. Here, we present SeqSero2 (github.com/denglab/SeqSero2; denglab.info/SeqSero2), an algorithmic transformation and functional update of the original SeqSero. Major improvements include (i) additional sequence markers for identification of Salmonella species and subspecies and certain serotypes, (ii) a k-mer based algorithm for rapid serotype prediction from raw reads (seconds per genome) and improved serotype prediction from assemblies, and (iii) a targeted assembly approach for specific retrieval of serotype determinants from WGS for serotype prediction, new allele discovery, and prediction troubleshooting. Evaluated using 5,794 genomes representing 364 common U.S. serotypes, including 2,280 human isolates of 117 serotypes from the National Antimicrobial Resistance Monitoring System, SeqSero2 is up to 50 times faster than the original SeqSero while maintaining equivalent accuracy for raw reads and substantially improving accuracy for assemblies. SeqSero2 further suggested that 3% of the tested genomes contained reads from multiple serotypes, indicating a use for contamination detection. In addition to short reads, SeqSero2 demonstrated potential for accurate and rapid serotype prediction directly from long nanopore reads despite base call errors. Testing of 40 nanopore-sequenced genomes of 17 serotypes yielded a single H antigen misidentification. IMPORTANCE Serotyping is the basis of public health surveillance of Salmonella. It remains a first-line subtyping method even as surveillance continues to be transformed by whole-genome sequencing. SeqSero allows the integration of Salmonella serotyping into a whole-genome-sequencing-based laboratory workflow while maintaining continuity with the classic serotyping scheme. SeqSero2, informed by extensive testing and application of SeqSero in the United States and other countries, incorporates important improvements and updates that further strengthen its application in routine and large-scale surveillance of Salmonella by whole-genome sequencing.

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Evaluation of Single-Molecule Sequencing Technologies for Structural Variant Detection in Two Swedish Human Genomes

Genes ◽

10.3390/genes11121444 ◽

2020 ◽

Vol 11 (12) ◽

pp. 1444

Author(s):

Nazeefa Fatima ◽

Anna Petri ◽

Ulf Gyllensten ◽

Lars Feuk ◽

Adam Ameur

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Single Molecule ◽

Large Scale ◽

Whole Genome Sequencing Data ◽

Whole Genome ◽

Sequencing Data ◽

Structural Variations ◽

Single Molecule Sequencing ◽

Human Samples

Long-read single molecule sequencing is increasingly used in human genomics research, as it allows to accurately detect large-scale DNA rearrangements such as structural variations (SVs) at high resolution. However, few studies have evaluated the performance of different single molecule sequencing platforms for SV detection in human samples. Here we performed Oxford Nanopore Technologies (ONT) whole-genome sequencing of two Swedish human samples (average 32× coverage) and compared the results to previously generated Pacific Biosciences (PacBio) data for the same individuals (average 66× coverage). Our analysis inferred an average of 17k and 23k SVs from the ONT and PacBio data, respectively, with a majority of them overlapping with an available multi-platform SV dataset. When comparing the SV calls in the two Swedish individuals, we find a higher concordance between ONT and PacBio SVs detected in the same individual as compared to SVs detected by the same technology in different individuals. Downsampling of PacBio reads, performed to obtain similar coverage levels for all datasets, resulted in 17k SVs per individual and improved overlap with the ONT SVs. Our results suggest that ONT and PacBio have a similar performance for SV detection in human whole genome sequencing data, and that both technologies are feasible for population-scale studies.

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The MOBSTER R package for tumour subclonal deconvolution from bulk DNA whole-genome sequencing data

BMC Bioinformatics ◽

10.1186/s12859-020-03863-1 ◽

2020 ◽

Vol 21 (1) ◽

Author(s):

Giulio Caravagna ◽

Guido Sanguinetti ◽

Trevor A. Graham ◽

Andrea Sottoriva

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Large Scale ◽

R Package ◽

Whole Genome Sequencing Data ◽

Whole Genome ◽

Sequencing Data ◽

Evolutionary Forces ◽

Evolutionary Trajectories ◽

Cancer Tissues

Abstract Background The large-scale availability of whole-genome sequencing profiles from bulk DNA sequencing of cancer tissues is fueling the application of evolutionary theory to cancer. From a bulk biopsy, subclonal deconvolution methods are used to determine the composition of cancer subpopulations in the biopsy sample, a fundamental step to determine clonal expansions and their evolutionary trajectories. Results In a recent work we have developed a new model-based approach to carry out subclonal deconvolution from the site frequency spectrum of somatic mutations. This new method integrates, for the first time, an explicit model for neutral evolutionary forces that participate in clonal expansions; in that work we have also shown that our method improves largely over competing data-driven methods. In this Software paper we present mobster, an open source R package built around our new deconvolution approach, which provides several functions to plot data and fit models, assess their confidence and compute further evolutionary analyses that relate to subclonal deconvolution. Conclusions We present the mobster package for tumour subclonal deconvolution from bulk sequencing, the first approach to integrate Machine Learning and Population Genetics which can explicitly model co-existing neutral and positive selection in cancer. We showcase the analysis of two datasets, one simulated and one from a breast cancer patient, and overview all package functionalities.

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Rainbow: a tool for large-scale whole-genome sequencing data analysis using cloud computing

BMC Genomics ◽

10.1186/1471-2164-14-425 ◽

2013 ◽

Vol 14 (1) ◽

pp. 425 ◽

Cited By ~ 32

Author(s):

Shanrong Zhao ◽

Kurt Prenger ◽

Lance Smith ◽

Thomas Messina ◽

Hongtao Fan ◽

...

Keyword(s):

Cloud Computing ◽

Data Analysis ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Large Scale ◽

Whole Genome Sequencing Data ◽

Whole Genome ◽

Sequencing Data ◽

Sequencing Data Analysis

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Atypical chromosome 22q11.2 deletions are complex rearrangements and have different mechanistic origins

Human Molecular Genetics ◽

10.1093/hmg/ddz166 ◽

2019 ◽

Vol 28 (22) ◽

pp. 3724-3733

Author(s):

Lisanne Vervoort ◽

Wolfram Demaerel ◽

Laura Y Rengifo ◽

Adrian Odrzywolski ◽

Elfi Vergaelen ◽

...

Keyword(s):

Homologous Recombination ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Large Scale ◽

Deletion Syndrome ◽

Whole Genome Sequencing Data ◽

Common Mechanism ◽

Small Subset ◽

Whole Genome ◽

Chromosome 22Q11.2

Abstract The majority (99%) of individuals with 22q11.2 deletion syndrome (22q11.2DS) have a deletion that is caused by non-allelic homologous recombination between two of four low copy repeat clusters on chromosome 22q11.2 (LCR22s). However, in a small subset of patients, atypical deletions are observed with at least one deletion breakpoint within unique sequence between the LCR22s. The position of the chromosome breakpoints and the mechanisms driving those atypical deletions remain poorly studied. Our large-scale, whole genome sequencing study of >1500 subjects with 22q11.2DS identified six unrelated individuals with atypical deletions of different types. Using a combination of whole genome sequencing data and fiber-fluorescence in situ hybridization, we mapped the rearranged alleles in these subjects. In four of them, the distal breakpoints mapped within one of the LCR22s and we found that the deletions likely occurred by replication-based mechanisms. Interestingly, in two of them, an inversion probably preceded inter-chromosomal ‘allelic’ homologous recombination between differently oriented LCR22-D alleles. Inversion associated allelic homologous recombination (AHR) may well be a common mechanism driving (atypical) deletions on 22q11.2.

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The project MinE databrowser: bringing large-scale whole-genome sequencing in ALS to researchers and the public

Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration ◽

10.1080/21678421.2019.1606244 ◽

2019 ◽

Vol 20 (5-6) ◽

pp. 432-440 ◽

Cited By ~ 14

Author(s):

Rick A.A. van der Spek ◽

Wouter van Rheenen ◽

Sara L. Pulit ◽

Kevin P. Kenna ◽

Leonard H. van den Berg ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Large Scale ◽

Whole Genome ◽

The Public

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The Project MinE databrowser: bringing large-scale whole-genome sequencing in ALS to researchers and the public

10.1101/377911 ◽

2018 ◽

Cited By ~ 1

Author(s):

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Large Scale ◽

Interactive Design ◽

Whole Genome ◽

Unique Combination ◽

The Public ◽

One Stop ◽

Als Patients ◽

Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a rapidly progressive fatal neurodegenerative disease affecting 1 in 350 people. The aim of Project MinE is to elucidate the pathophysiology of ALS through whole-genome sequencing at least 15,000 ALS patients and 7,500 controls at 30X coverage. Here, we present the Project MinE data browser (databrowser.projectmine.com). a unique and intuitive one-stop, open-access server that provides detailed information on genetic variation analyzed in a new and still growing set of 4,366 ALS cases and 1,832 matched controls. Through its visual components and interactive design, the browser specifically aims to be a resource to those without a biostatistics background and allow clinicians and preclinical researchers to integrate Project MinE data into their own research. The browser allows users to query a transcript and immediately access a unique combination of detailed (meta)data, annotations and association statistics that would otherwise require analytic expertise and visits to scattered resources.

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