Fungal genomics and transcriptomics

2017 ◽  
Author(s):  
Carol A. Munro ◽  
Duncan Wilson
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Large Scale ◽  
Pathogenic Fungi ◽  
Whole Genome ◽  
Scale Analysis ◽  
Fungal Genomics ◽  
Large Scale Analysis ◽  
Fungal Biology

The advent of whole-genome sequencing has resulted in a range of platforms for large-scale analysis of the DNA (genomics), RNA (transcriptomics), protein (proteomics), and metabolite (metabolomics) content of cells. These inclusive ‘omics’ approaches have allowed for unparalleled insights into fungal biology. In this chapter we will discuss how genomics and transcriptomics have been used to broaden our understanding of the biology of human pathogenic fungi and their interactions with their hosts.

scholarly journals Comparing serotyping with whole-genome sequencing for subtyping of non-typhoidal Salmonella enterica: a large-scale analysis of 37 serotypes with a public health impact in the USA

2020 ◽  
Vol 6 (9) ◽  
Author(s):  
Ehud Elnekave ◽  
Samuel L. Hong ◽  
Seunghyun Lim ◽  
Timothy J. Johnson ◽  
Andres Perez ◽  
...  
Keyword(s):  
Public Health ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Large Scale ◽  
Health Impact ◽  
Public Health Impact ◽  
Whole Genome ◽  
Scale Analysis ◽  
Large Scale Analysis ◽  
The Usa

Serotyping has traditionally been used for subtyping of non-typhoidal Salmonella (NTS) isolates. However, its discriminatory power is limited, which impairs its use for epidemiological investigations of source attribution. Whole-genome sequencing (WGS) analysis allows more accurate subtyping of strains. However, because of the relative newness and cost of routine WGS, large-scale studies involving NTS WGS are still rare. We aimed to revisit the big picture of subtyping NTS with a public health impact by using traditional serotyping (i.e. reaction between antisera and surface antigens) and comparing the results with those obtained using WGS. For this purpose, we analysed 18 282 sequences of isolates belonging to 37 serotypes with a public health impact that were recovered in the USA between 2006 and 2017 from multiple sources, and were available at the National Center for Biotechnology Information (NCBI). Phylogenetic trees were reconstructed for each serotype using the core genome for the identification of genetic subpopulations. We demonstrated that WGS-based subtyping allows better identification of sources potentially linked with human infection and emerging subpopulations, along with providing information on the risk of dissemination of plasmids and acquired antimicrobial resistance genes (AARGs). In addition, by reconstructing a phylogenetic tree with representative isolates from all serotypes (n=370), we demonstrated genetic variability within and between serotypes, which formed monophyletic, polyphyletic and paraphyletic clades. Moreover, we found (in the entire data set) an increased detection rate for AARGs linked to key antimicrobials (such as quinolones and extended-spectrum cephalosporins) over time. The outputs of this large-scale analysis reveal new insights into the genetic diversity within and between serotypes; the polyphyly and paraphyly of certain serotypes may suggest that the subtyping of NTS to serotypes may not be sufficient. Moreover, the results and the methods presented here, leading to differentiation between genetic subpopulations based on their potential risk to public health, as well as narrowing down the possible sources of these infections, may be used as a baseline for subtyping of future NTS infections and help efforts to mitigate and prevent infections in the USA and globally.

0306 Exploring the feasibility of using copy number variants as genetic markers through large-scale whole genome sequencing experiments

2016 ◽  
Vol 94 (suppl_5) ◽  
pp. 146-146
Author(s):  
D. M. Bickhart ◽  
L. Xu ◽  
J. L. Hutchison ◽  
J. B. Cole ◽  
D. J. Null ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genetic Markers ◽  
Genome Sequencing ◽  
Copy Number ◽  
Large Scale ◽  
Copy Number Variants ◽  
Whole Genome

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

2019 ◽  
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

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.

Genomic sequences for fungi.

2021 ◽  
pp. 231-254
Author(s):  
Riccardo Baroncelli ◽  
Giovanni Cafà
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Fungal Genome ◽  
Basic Knowledge ◽  
Genomic Sequences ◽  
Whole Genome ◽  
Fungal Genomics

Abstract This chapter aims to give an overview of the basic knowledge, understanding and perspectives in fungal genomics. It is likely that fungal genome sequencing will soon become simpler and cheaper, and allow most research laboratories to undertake in-house, whole genome sequencing on a regular basis, as sequencers will be accessible to most laboratories. Nonetheless, most of the innovation in the next decade will be driven by theories in innovative perspectives and fields of investigation, rather than in novel technical approaches.

scholarly journals Recombinational Switching of the Clostridium difficile S-Layer and a Novel Glycosylation Gene Cluster Revealed by Large-Scale Whole-Genome Sequencing

2012 ◽  
Vol 207 (4) ◽  
pp. 675-686 ◽  
Author(s):  
Kate E. Dingle ◽  
Xavier Didelot ◽  
M. Azim Ansari ◽  
David W. Eyre ◽  
Alison Vaughan ◽  
...  
Keyword(s):  
Clostridium Difficile ◽  
Whole Genome Sequencing ◽  
Gene Cluster ◽  
Genome Sequencing ◽  
Large Scale ◽  
Whole Genome

scholarly journals Whole-Genome Sequencing for Routine Pathogen Surveillance in Public Health: a Population Snapshot of InvasiveStaphylococcus aureusin Europe

mBio ◽  
2016 ◽  
Vol 7 (3) ◽  
Author(s):  
David M. Aanensen ◽  
Edward J. Feil ◽  
Matthew T. G. Holden ◽  
Janina Dordel ◽  
Corin A. Yeats ◽  
...  
Keyword(s):  
Public Health ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Large Scale ◽  
Bacterial Pathogens ◽  
Epidemiological Surveillance ◽  
Data Sets ◽  
Whole Genome ◽  
Bioinformatic Tools ◽  
Road Map

ABSTRACTThe implementation of routine whole-genome sequencing (WGS) promises to transform our ability to monitor the emergence and spread of bacterial pathogens. Here we combined WGS data from 308 invasiveStaphylococcus aureusisolates corresponding to a pan-European population snapshot, with epidemiological and resistance data. Geospatial visualization of the data is made possible by a generic software tool designed for public health purposes that is available at the project URL (http://www.microreact.org/project/EkUvg9uY?tt=rc). Our analysis demonstrates that high-risk clones can be identified on the basis of population level properties such as clonal relatedness, abundance, and spatial structuring and by inferring virulence and resistance properties on the basis of gene content. We also show thatin silicopredictions of antibiotic resistance profiles are at least as reliable as phenotypic testing. We argue that this work provides a comprehensive road map illustrating the three vital components for future molecular epidemiological surveillance: (i) large-scale structured surveys, (ii) WGS, and (iii) community-oriented database infrastructure and analysis tools.IMPORTANCEThe spread of antibiotic-resistant bacteria is a public health emergency of global concern, threatening medical intervention at every level of health care delivery. Several recent studies have demonstrated the promise of routine whole-genome sequencing (WGS) of bacterial pathogens for epidemiological surveillance, outbreak detection, and infection control. However, as this technology becomes more widely adopted, the key challenges of generating representative national and international data sets and the development of bioinformatic tools to manage and interpret the data become increasingly pertinent. This study provides a road map for the integration of WGS data into routine pathogen surveillance. We emphasize the importance of large-scale routine surveys to provide the population context for more targeted or localized investigation and the development of open-access bioinformatic tools to provide the means to combine and compare independently generated data with publicly available data sets.

scholarly journals Fast and inexpensive whole genome sequencing library preparation from intact yeast cells

2020 ◽  
Author(s):  
Sibylle C Vonesch ◽  
Shengdi Li ◽  
Chelsea Szu Tu ◽  
Bianca P Hennig ◽  
Nikolay Dobrev ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Genomic Dna ◽  
Large Scale ◽  
Massively Parallel Sequencing ◽  
Yeast Cells ◽  
Whole Genome ◽  
High Quality ◽  
Rapid Preparation ◽  
Yeast Cultures

ABSTRACTThrough the increase in the capacity of sequencing machines massively parallel sequencing of thousands of samples in a single run is now possible. With the improved throughput and resulting drop in the price of sequencing, the cost and time for preparation of sequencing libraries have become the major bottleneck in large-scale experiments. Methods using a hyperactive variant of the Tn5 transposase efficiently generate libraries starting from cDNA or genomic DNA in a few hours and are highly scalable. For genome sequencing, however, the time and effort spent on genomic DNA isolation limits the practicability of sequencing large numbers of samples. Here, we describe a highly scalable method for preparing high quality whole-genome sequencing libraries directly from yeast cultures in less than three hours at 34 cents per sample. We skip the rate-limiting step of genomic DNA extraction by directly tagmenting yeast spheroplasts and add a nucleosome release step prior to enrichment PCR to improve the evenness of genomic coverage. Resulting libraries do not show any GC-bias and are comparable in quality to libraries processed from genomic DNA with a commercially available Tn5-based kit. We use our protocol to investigate CRISPR/Cas9 on- and off-target edits and reliably detect edited variants and shared polymorphisms between strains. Our protocol enables rapid preparation of unbiased and high-quality, sequencing-ready indexed libraries for hundreds of yeast strains in a single day at a low price. By adjusting individual steps of our workflow we expect that our protocol can be adapted to other organisms.

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