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A quantitative hybridization approach using 17 DNA markers for identification and clustering analysis of Ralstonia solanacearum
Author(s) -
Albuquerque P.,
Marcal A. R. S.,
Caridade C.,
Costa R.,
Mendes M. V.,
Tavares F.
Publication year - 2015
Publication title -
plant pathology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.928
H-Index - 85
eISSN - 1365-3059
pISSN - 0032-0862
DOI - 10.1111/ppa.12386
Subject(s) - biology , ralstonia solanacearum , typing , genotyping , computational biology , genetics , dendrogram , multilocus sequence typing , polymerase chain reaction , in silico , genetic marker , genome , genotype , genetic diversity , pathogen , gene , population , demography , sociology
Ralstonia solanacearum (Rs) is a quarantine phytopathogenic bacterium accountable for heavy economic losses worldwide. Monitoring and eradication programmes required for this pathogen are dependent on the availability of time‐ and cost‐efficient detection and typing methods. However, members of the Rs species complex are characterized by a high phenotypic and genetic diversity, which requires improved diagnostics methods. The currently available full genome sequences of several Rs strains allow for the selection of novel specific DNA markers using comparative genomics tools. In this work, 17 novel markers were selected based on Rs‐specific protein domains and thoroughly validated for specificity and stability, both in silico and using ‘wet lab’ assays. Polymerase chain reaction‐ and hybridization‐based validation assays revealed that the DNA regions selected as markers were unevenly distributed amongst the tested strains, with nine markers present throughout the species complex. The distribution of the remaining eight markers was highly variable between the different analysed strains and enabled the attainment of strain‐specific dot blot hybridization patterns, particularly informative for typing. The average probability value of each strain being positive for each of the 17 markers was calculated by an algorithm and used to obtain a dendrogram representing hierarchical clustering analysis of Rs, according to the similarity of their hybridization patterns. This method should prove to be a robust and straightforward procedure for genotyping members of the Rs species complex. Furthermore, this quantitative hybridization approach will allow the construction of informative databases to determine new Rs genotypes and infer epidemiological patterns.