Journal article
Development of the Automated Primer Design Workflow Uniqprimer and Diagnostic Primers for the Broad-Host-Range Plant Pathogen Dickeya dianthicola
Plant disease, Vol.103(11), pp.2893-2902
11/2019
PMID: 31436473
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Source: InCites
Abstract
Uniqprimer, a software pipeline developed in Python, was deployed as a user-friendly interne tool in Rice Galaxy for comparative genome analyses to design primer sets for PCRassays capable of detecting target bacterial taxa. The pipeline was trialed with Dickeya dianthicola, a destructive broad-host-range bacterial pathogen found in most potato growing regions. Dickeya is a highly variable genus, and some primers available to detect this genus and species exhibit common diagnostic failures. Upon uploading a selection of target and nontarget genomes, six primer sets were rapidly identified with Uniqprimer, of which two were specific and sensitive when tested with D. dianthicola. The remaining four amplified a minority of the nontarget strains tested. The two promising candidate primer sets were trialed with DNA isolated from 116 field samples from across the United States that were previously submitted for testing. D. dianthicola was detected in 41 samples, demonstrating the applicability of our detection primers and suggesting widespread occurrence of D. dianthicola in North America.
Details
- Title
- Development of the Automated Primer Design Workflow Uniqprimer and Diagnostic Primers for the Broad-Host-Range Plant Pathogen Dickeya dianthicola
- Creators
- Shaista Karim - Colorado State UniversityR. Ryan McNally - Colorado State UniversityAfnan S. Nasaruddin - Colorado State UniversityAlexis DeReeper - University of MontpellierRamil P. Mauleon - International Rice Research InstituteAmy O. Charkowski - Colorado State UniversityJan E. Leach - Colorado State UniversityAsa Ben-Hur - Colorado State UniversityLindsay R. Triplett - Connecticut Agricultural Experiment Station
- Publication Details
- Plant disease, Vol.103(11), pp.2893-2902
- Publisher
- Amer Phytopathological Soc
- Number of pages
- 10
- Grant note
- 2017-51181-26827 / USDA Specialty Crops Research Initiative project International Rice Informatics Consortium IRD 2017-68008-26731 / CARE project United States Department of Agriculture Agricultural Research Service; United States Department of Agriculture (USDA); USDA Agricultural Research Service CGIAR Excellence in Breeding Platform; CGIAR Faculty Development Program at the University of Agriculture, Faisalabad, Pakistan Animal and Plant Health Inspection Service Taiwan Council of Agriculture Grant Genomic Open-source Breeding Informatics Initiative project
- Identifiers
- 991013099200602368
- Copyright
- © 2019 The American Phytopathological Society.
- Academic Unit
- Faculty of Science and Engineering
- Language
- English
- Resource Type
- Journal article