Recombination Events Shape the Genomic Evolution of Infectious Bronchitis Virus in Europe

Infectious bronchitis of chicken is a high morbidity and mortality viral disease affecting the poultry industry worldwide; therefore, a better understanding of this pathogen is of utmost importance. The primary aim of this study was to obtain a deeper insight into the genomic diversity of field infectious bronchitis virus (IBV) strains using phylogenetic and recombination analysis. We sequenced the genome of 20 randomly selected strains from seven European countries. After sequencing, we created a genome sequence data set that contained 36 European origin field isolates and 33 vaccine strains. When analyzing these 69 IBV genome sequences, we identified 215 recombination events highlighting that some strains had multiple recombination breaking points. Recombination hot spots were identified mostly in the regions coding for non-structural proteins, and multiple recombination hot spots were identified in the nsp2, nsp3, nsp8, and nsp12 coding regions. Recombination occurred among different IBV genotypes and involved both field and vaccine IBV strains. Ninety percent of field strains and nearly half of vaccine strains showed evidence of recombination. Despite the low number and the scattered geographical and temporal origin of whole-genome sequence data collected from European Gammacoronaviruses, this study underlines the importance of recombination as a major evolutionary mechanism of IBVs.

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Use of Whole-Genus Genome Sequence Data To Develop a Multilocus Sequence Typing Tool That Accurately Identifies Yersinia Isolates to the Species and Subspecies Levels

Journal of Clinical Microbiology ◽

10.1128/jcm.02395-14 ◽

2014 ◽

Vol 53 (1) ◽

pp. 35-42 ◽

Cited By ~ 22

Author(s):

Miquette Hall ◽

Marie A. Chattaway ◽

Sandra Reuter ◽

Cyril Savin ◽

Eckhard Strauch ◽

...

Keyword(s):

Genome Sequence ◽

Multilocus Sequence Typing ◽

Sequence Data ◽

Species Level ◽

Reference Laboratory ◽

Whole Genome ◽

Pathogenic Species ◽

Data Set ◽

Content Type ◽

Genome Sequence Data

The genusYersiniais a large and diverse bacterial genus consisting of human-pathogenic species, a fish-pathogenic species, and a large number of environmental species. Recently, the phylogenetic and population structure of the entire genus was elucidated through the genome sequence data of 241 strains encompassing every known species in the genus. Here we report the mining of this enormous data set to create a multilocus sequence typing-based scheme that can identifyYersiniastrains to the species level to a level of resolution equal to that for whole-genome sequencing. Our assay is designed to be able to accurately subtype the important human-pathogenic speciesYersinia enterocoliticato whole-genome resolution levels. We also report the validation of the scheme on 386 strains from reference laboratory collections across Europe. We propose that the scheme is an important molecular typing system to allow accurate and reproducible identification ofYersiniaisolates to the species level, a process often inconsistent in nonspecialist laboratories. Additionally, our assay is the most phylogenetically informative typing scheme available forY. enterocolitica.

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Use of Whole Genome Sequence Data To Infer Baculovirus Phylogeny

Journal of Virology ◽

10.1128/jvi.75.17.8117-8126.2001 ◽

2001 ◽

Vol 75 (17) ◽

pp. 8117-8126 ◽

Cited By ~ 234

Author(s):

Elisabeth A. Herniou ◽

Teresa Luque ◽

Xinwen Chen ◽

Just M. Vlak ◽

Doreen Winstanley ◽

...

Keyword(s):

Genome Sequence ◽

Sequence Data ◽

Gene Content ◽

Whole Genome Sequence ◽

Whole Genome ◽

Data Set ◽

Genome Sequence Data ◽

Distance Analysis ◽

Group I ◽

Using Data

ABSTRACT Several phylogenetic methods based on whole genome sequence data were evaluated using data from nine complete baculovirus genomes. The utility of three independent character sets was assessed. The first data set comprised the sequences of the 63 genes common to these viruses. The second set of characters was based on gene order, and phylogenies were inferred using both breakpoint distance analysis and a novel method developed here, termed neighbor pair analysis. The third set recorded gene content by scoring gene presence or absence in each genome. All three data sets yielded phylogenies supporting the separation of the Nucleopolyhedrovirus (NPV) andGranulovirus (GV) genera, the division of the NPVs into groups I and II, and species relationships within group I NPVs. Generation of phylogenies based on the combined sequences of all 63 shared genes proved to be the most effective approach to resolving the relationships among the group II NPVs and the GVs. The history of gene acquisitions and losses that have accompanied baculovirus diversification was visualized by mapping the gene content data onto the phylogenetic tree. This analysis highlighted the fluid nature of baculovirus genomes, with evidence of frequent genome rearrangements and multiple gene content changes during their evolution. Of more than 416 genes identified in the genomes analyzed, only 63 are present in all nine genomes, and 200 genes are found only in a single genome. Despite this fluidity, the whole genome-based methods we describe are sufficiently powerful to recover the underlying phylogeny of the viruses.

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Faculty Opinions recommendation of Optimal algorithms for haplotype assembly from whole-genome sequence data.

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

10.3410/f.13339986.14707085 ◽

2011 ◽

Author(s):

Alejandro Schaffer

Keyword(s):

Genome Sequence ◽

Sequence Data ◽

Whole Genome Sequence ◽

Whole Genome ◽

Optimal Algorithms ◽

Genome Sequence Data ◽

Haplotype Assembly

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Faculty Opinions recommendation of Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis.

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

10.3410/f.726028125.793519670 ◽

2016 ◽

Author(s):

Lars Malmstroem

Keyword(s):

Staphylococcus Aureus ◽

Antibiotic Resistance ◽

Mycobacterium Tuberculosis ◽

Genome Sequence ◽

Sequence Data ◽

Genome Sequence Data

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TIGER: inferring DNA replication timing from whole-genome sequence data

Bioinformatics ◽

10.1093/bioinformatics/btab166 ◽

2021 ◽

Cited By ~ 1

Author(s):

Amnon Koren ◽

Dashiell J Massey ◽

Alexa N Bracci

Keyword(s):

Dna Replication ◽

Genome Sequence ◽

Genomic Dna ◽

Sequence Data ◽

Replication Timing ◽

Whole Genome Sequence ◽

Supplementary Information ◽

Whole Genome ◽

Genome Sequence Data ◽

Dna Replication Timing

Abstract Motivation Genomic DNA replicates according to a reproducible spatiotemporal program, with some loci replicating early in S phase while others replicate late. Despite being a central cellular process, DNA replication timing studies have been limited in scale due to technical challenges. Results We present TIGER (Timing Inferred from Genome Replication), a computational approach for extracting DNA replication timing information from whole genome sequence data obtained from proliferating cell samples. The presence of replicating cells in a biological specimen leads to non-uniform representation of genomic DNA that depends on the timing of replication of different genomic loci. Replication dynamics can hence be observed in genome sequence data by analyzing DNA copy number along chromosomes while accounting for other sources of sequence coverage variation. TIGER is applicable to any species with a contiguous genome assembly and rivals the quality of experimental measurements of DNA replication timing. It provides a straightforward approach for measuring replication timing and can readily be applied at scale. Availability and Implementation TIGER is available at https://github.com/TheKorenLab/TIGER. Supplementary information Supplementary data are available at Bioinformatics online

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