Pan-genome sequence analysis using Panseq: an online tool for the rapid analysis of core and accessory genomic regions

Laing, Chad R.; Buchanan, Cody; Taboada, Eduardo N.; Zhang, Yongxiang; Kropinski, Andrew M.; Villegas, André; Thomas, James E.; Gannon, Victor P. J.

doi:10.1186/1471-2105-11-461

Cited by 248 publications

(233 citation statements)

References 47 publications

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“…Unique sequences were identified based on alignments of homologous sequences performed using SeqMan software (Lasergene 8; DNASTAR Inc.). Somatic probes were designed based on publicly available sequences and on sequences determined inhouse for gene targets (Table 2) (32). Similarly, a unique rhs-like gene sequence (SG1045) of Salmonella Gallinarum (NC_011274) was used to design a serovar-specific probe.…”

Section: Resultsmentioning

confidence: 99%

Rapid Genoserotyping Tool for Classification of Salmonella Serovars

et al. 2011

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We have developed a Salmonella genoserotyping array (SGSA) which rapidly generates an antigenic formula consistent with the White-Kauffmann-Le Minor scheme, currently the gold standard for Salmonella serotyping. A set of 287 strains representative of 133 Salmonella serovars was assembled to validate the array and to test the array probes for accuracy, specificity, and reproducibility. Initially, 76 known serovars were utilized to validate the specificity and repeatability of the array probes and their expected probe patterns. The SGSA generated the correct serovar designations for 100% of the known subspecies I serovars tested in the validation panel and an antigenic formula consistent with that of the White-Kauffmann-Le Minor scheme for 97% of all known serovars tested. Once validated, the SGSA was assessed against a blind panel of 100 Salmonella enterica subsp. I samples serotyped using traditional methods. In summary, the SGSA correctly identified all of the blind samples as representing Salmonella and successfully identified 92% of the antigens found within the unknown samples. Antigen-and serovar-specific probes, in combination with a pepT PCR for confirmation of S. enterica subsp. Enteritidis determinations, generated an antigenic formula and/or a serovar designation consistent with the White-Kauffmann-Le Minor scheme for 87% of unknown samples tested with the SGSA. Future experiments are planned to test the specificity of the array probes with other Salmonella serovars to demonstrate the versatility and utility of this array as a public health tool in the identification of Salmonella.

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Section: Resultsmentioning

confidence: 99%

Rapid Genoserotyping Tool for Classification of Salmonella Serovars

et al. 2011

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“…Core and accessory genomes were estimated using whole genes and 250 base windows, identified using PANSEQ (55), as the unit of comparison. These approaches gave similar results, and PANSEQ results are used here (Fig.…”

Section: Methodsmentioning

confidence: 99%

Benefit of transferred mutations is better predicted by the fitness of recipients than by their ecological or genetic relatedness

Wang

Arenas

Stoebel

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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The effect of a mutation depends on its interaction with the genetic background in which it is assessed. Studies in experimental systems have demonstrated that such interactions are common among beneficial mutations and often follow a pattern consistent with declining evolvability of more fit genotypes. However, these studies generally examine the consequences of interactions between a small number of focal mutations. It is not clear, therefore, that findings can be extrapolated to natural populations, where new mutations may be transferred between genetically divergent backgrounds. We build on work that examined interactions between four beneficial mutations selected in a laboratory-evolved population of Escherichia coli to test how they interact with the genomes of diverse natural isolates of the same species. We find that the fitness effect of transferred mutations depends weakly on the genetic and ecological similarity of recipient strains relative to the donor strain in which the mutations were selected. By contrast, mutation effects were strongly inversely correlated to the initial fitness of the recipient strain. That is, there was a pattern of diminishing returns whereby fit strains benefited proportionally less from an added mutation. Our results strengthen the view that the fitness of a strain can be a major determinant of its ability to adapt. They also support a role for barriers of transmission, rather than differential selection of transferred DNA, as an explanation of observed phylogenetically determined patterns of restricted recombination among E. coli strains.

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“…The genomes are classified according to geographic location (Atlantic vs Pacific) and environment type (oil reservoir vs marine vent). For networks (a) and (b), the data were obtained using PanSeq (Laing et al, 2010). Core SNPs were required to be present in all 7 genomes, whereas the genomic fragments were considered shared if they were at least 80% identical.…”

Section: Resultsmentioning

confidence: 99%

“…Pan-genome calculations were performed in Panseq (Laing et al, 2010) using a fragment size of 500 bp and 80% identity cutoff for the analyses of TM-group genomes, and 90% identity cutoff for the analyses of TM-group and genomes assembled from metagenomes (to confidently exclude possible contamination). The data matrices of shared core SNPs and shared 500 bp fragments were converted into uncorrected distances and visualized in SplitsTree 4 (Huson and Bryant, 2006) using NeighborNet clustering.…”

Section: Gene Content and Genome Alignmentsmentioning

confidence: 99%

Evidence for extensive gene flow and Thermotoga subpopulations in subsurface and marine environments

et al. 2014

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Oil reservoirs represent a nutrient-rich ecological niche of the deep biosphere. Although most oil reservoirs are occupied by microbial populations, when and how the microbes colonized these environments remains unanswered. To address this question, we compared 11 genomes of Thermotoga maritima-like hyperthermophilic bacteria from two environment types: subsurface oil reservoirs in the North Sea and Japan, and marine sites located in the Kuril Islands, Italy and the Azores. We complemented our genomes with Thermotoga DNA from publicly available subsurface metagenomes from North America and Australia. Our analysis revealed complex non-bifurcating evolutionary history of the isolates' genomes, suggesting high amounts of gene flow across all sampled locations, a conjecture supported by numerous recombination events. Genomes from the same type of environment tend to be more similar, and have exchanged more genes with each other than with geographically close isolates from different types of environments. Hence, Thermotoga populations of oil reservoirs do not appear isolated, a requirement of the 'burial and isolation' hypothesis, under which reservoir bacteria are descendants of the isolated communities buried with sediments that over time became oil reservoirs. Instead, our analysis supports a more complex view, where bacteria from subsurface and marine populations have been continuously migrating into the oil reservoirs and influencing their genetic composition. The Thermotoga spp. in the oil reservoirs in the North Sea and Japan probably entered the reservoirs shortly after they were formed. An Australian oil reservoir, on the other hand, was likely colonized very recently, perhaps during human reservoir development.

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Pan-genome sequence analysis using Panseq: an online tool for the rapid analysis of core and accessory genomic regions

Cited by 248 publications

References 47 publications

Rapid Genoserotyping Tool for Classification of Salmonella Serovars

Rapid Genoserotyping Tool for Classification of Salmonella Serovars

Benefit of transferred mutations is better predicted by the fitness of recipients than by their ecological or genetic relatedness

Evidence for extensive gene flow and Thermotoga subpopulations in subsurface and marine environments

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