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Published on: March 11, 2020
How to Conduct Phylogenetic Endoglucanase (egl) Inference Using the Reference Ralstonia solanacearum Species Complex
Gilles Cellier1, Miharisoa Mirana Gauche2, Jean Jacques Cheron3
1Anses Laboratoire de la sante des vegetaux - Saint-Pierre de la Reunion, Laboratoire de la Sante des Vegetaux, 7 chemin de l'IRAT, Pole de Protection des Plantes, Saint Pierre, Réunion, 97410; gilles.cellier@anses.fr.
Accurate classification of Ralstonia solanacearum species complex (RSSC) strains is crucial for plant disease research. This study provides a curated database and methodology for reliable endoglucanase gene-based sequevar typing of RSSC.
Area of Science:
- Microbiology
- Plant Pathology
- Genetics
Background:
- The Ralstonia solanacearum species complex (RSSC) is a significant group of plant pathogens.
- Recent taxonomic revisions have divided the RSSC into three distinct species.
- Phylotype and sequevar classifications, based on DNA and the endoglucanase (egl) gene, are used for strain differentiation.
Purpose of the Study:
- To address the need for standardized and reliable sequevar assignment within the RSSC.
- To provide a curated database of endoglucanase (egl) gene sequences for RSSC.
- To establish a robust methodology for phylogenetic inference and sequevar determination.
Main Methods:
- Utilized endoglucanase (egl) gene sequencing for phylogenetic analysis.
- Developed and curated a reference database of egl sequences.
- Implemented a methodology for reproducible phylogenetic inference and sequevar assignment.
Main Results:
- A publicly accessible database of curated egl reference sequences for RSSC was established.
- A reliable methodology for phylogenetic inference and sequevar assignment was provided.
- The database and methods facilitate accurate strain typing and diversity assessment.
Conclusions:
- The developed database and methodology enhance the accuracy and reproducibility of RSSC strain typing.
- This resource is vital for researchers studying RSSC diversity and plant diseases.
- Standardized sequevar assignment prevents errors and improves the quality of research findings.
